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| 1. The false omission rate of a test is 95% and its specificity is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 2. The sensitivity of a test is 95%. | |
| We also know that the test's false omission rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 3. The sensitivity of a test is 85% and its precision is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the false omission rate of the test? | |
| 4. The precision of a test is 95% and its false omission rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 5. The specificity of a test is 95%. | |
| We also know that the test's negative predictive value is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 6. The false discovery rate of a test is 90% and its sensitivity is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 7. The false omission rate of a test is 95% and its precision is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 8. The false positive rate of a test is 90% and its sensitivity is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 9. The false positive rate of a test is 85% and its false omission rate is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the precision of the test? | |
| 10. The sensitivity of a test is 95% and its false omission rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 11. The precision of a test is 85% and its false negative rate is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the specificity of the test? | |
| 12. The false positive rate of a test is 95%. | |
| We also know that the test's sensitivity is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 13. The false negative rate of a test is 85% and its specificity is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 14. The sensitivity of a test is 85% and its specificity is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 15. The specificity of a test is 85% and its false omission rate is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 16. The false negative rate of a test is 85% and its false discovery rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the specificity of the test? | |
| 17. The negative predictive value of a test is 85% and its false negative rate is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the specificity of the test? | |
| 18. The precision of a test is 90%. | |
| We also know that the test's sensitivity is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 19. The false discovery rate of a test is 85% and its false negative rate is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the sensitivity of the test? | |
| 20. The false discovery rate of a test is 90% and its specificity is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the negative predictive value of the test? | |
| 21. The false positive rate of a test is 90% and its false discovery rate is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 22. The false positive rate of a test is 95% and its false discovery rate is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the false negative rate of the test? | |
| 23. The negative predictive value of a test is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 24. The false positive rate of a test is 95% and its precision is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 25. The sensitivity of a test is 95% and its negative predictive value is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 26. The specificity of a test is 90% and its false omission rate is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 27. The false omission rate of a test is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 28. The false positive rate of a test is 90% and its precision is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 29. The precision of a test is 85%. | |
| We also know that the test's specificity is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 30. The specificity of a test is 85% and its false negative rate is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 31. The specificity of a test is 90% and its false omission rate is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 32. The false discovery rate of a test is 85% and its negative predictive value is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the specificity of the test? | |
| 33. The false positive rate of a test is 95% and its sensitivity is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 34. The false negative rate of a test is 90% and its negative predictive value is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the precision of the test? | |
| 35. The false negative rate of a test is 90% and its false discovery rate is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 36. The false negative rate of a test is 95% and its precision is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 37. The specificity of a test is 95% and its negative predictive value is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 38. The precision of a test is 95% and its false omission rate is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 39. The precision of a test is 90%. | |
| We also know that the test's specificity is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 40. The false negative rate of a test is 95% and its precision is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the false omission rate of the test? | |
| 41. The precision of a test is 95% and its specificity is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 42. The specificity of a test is 85% and its sensitivity is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the precision of the test? | |
| 43. The negative predictive value of a test is 90% and its precision is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the specificity of the test? | |
| 44. The false omission rate of a test is 85%. | |
| We also know that the test's false negative rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 45. The false positive rate of a test is 85% and its false omission rate is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the false negative rate of the test? | |
| 46. The false discovery rate of a test is 95% and its sensitivity is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 47. The specificity of a test is 85%. | |
| We also know that the test's precision is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 48. The specificity of a test is 90% and its precision is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the false discovery rate of the test? | |
| 49. The false omission rate of a test is 90%. | |
| We also know that the test's precision is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 50. The false discovery rate of a test is 90%. | |
| We also know that the test's specificity is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 51. The negative predictive value of a test is 95% and its precision is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 52. The false discovery rate of a test is 85%. | |
| We also know that the test's false positive rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 53. The specificity of a test is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 54. The specificity of a test is 85% and its precision is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the false omission rate of the test? | |
| 55. The false omission rate of a test is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 56. The false negative rate of a test is 90% and its precision is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the false omission rate of the test? | |
| 57. The false omission rate of a test is 85%. | |
| We also know that the test's specificity is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 58. The false positive rate of a test is 85%. | |
| We also know that the test's negative predictive value is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 59. The negative predictive value of a test is 90% and its false discovery rate is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 60. The sensitivity of a test is 90% and its precision is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the specificity of the test? | |
| 61. The false positive rate of a test is 90%. | |
| We also know that the test's false negative rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 62. The negative predictive value of a test is 90% and its precision is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 63. The specificity of a test is 90% and its false negative rate is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 64. The negative predictive value of a test is 95%. | |
| We also know that the test's false discovery rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 65. The specificity of a test is 85% and its false negative rate is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the sensitivity of the test? | |
| 66. The sensitivity of a test is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 67. The specificity of a test is 90% and its false discovery rate is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the precision of the test? | |
| 68. The false positive rate of a test is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 69. The false negative rate of a test is 85%. | |
| We also know that the test's negative predictive value is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 70. The specificity of a test is 95% and its negative predictive value is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the false omission rate of the test? | |
| 71. The false positive rate of a test is 85%. | |
| We also know that the test's sensitivity is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 72. The false discovery rate of a test is 85% and its specificity is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 73. The false discovery rate of a test is 95% and its specificity is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 74. The specificity of a test is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 75. The sensitivity of a test is 85%. | |
| We also know that the test's precision is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 76. The false positive rate of a test is 95% and its negative predictive value is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the false negative rate of the test? | |
| 77. The false omission rate of a test is 95%. | |
| We also know that the test's sensitivity is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 78. The false discovery rate of a test is 85% and its negative predictive value is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the specificity of the test? | |
| 79. The sensitivity of a test is 85%. | |
| We also know that the test's false discovery rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 80. The false omission rate of a test is 95%. | |
| We also know that the test's false negative rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 81. The sensitivity of a test is 85% and its precision is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the false discovery rate of the test? | |
| 82. The false negative rate of a test is 95% and its precision is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 83. The false discovery rate of a test is 85% and its sensitivity is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the false omission rate of the test? | |
| 84. The false omission rate of a test is 85%. | |
| We also know that the test's specificity is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 85. The false positive rate of a test is 85% and its sensitivity is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 86. The false discovery rate of a test is 90%. | |
| We also know that the test's false negative rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 87. The false discovery rate of a test is 95% and its negative predictive value is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the false negative rate of the test? | |
| 88. The false positive rate of a test is 90% and its negative predictive value is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the false discovery rate of the test? | |
| 89. The precision of a test is 85%. | |
| We also know that the test's specificity is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 90. The negative predictive value of a test is 85%. | |
| We also know that the test's specificity is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 91. The false positive rate of a test is 90% and its false negative rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the negative predictive value of the test? | |
| 92. The specificity of a test is 90% and its false negative rate is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 93. The false negative rate of a test is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 94. The false negative rate of a test is 90% and its negative predictive value is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the specificity of the test? | |
| 95. The precision of a test is 85%. | |
| We also know that the test's false omission rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 96. The false discovery rate of a test is 95% and its false negative rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the sensitivity of the test? | |
| 97. The specificity of a test is 95%. | |
| We also know that the test's false discovery rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 98. The false omission rate of a test is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 99. The false omission rate of a test is 95% and its false negative rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the specificity of the test? | |
| 100. The false discovery rate of a test is 95% and its specificity is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the sensitivity of the test? | |
| 101. The false negative rate of a test is 90% and its negative predictive value is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the false positive rate of the test? | |
| 102. The false omission rate of a test is 85% and its sensitivity is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 103. The false positive rate of a test is 85% and its false negative rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the precision of the test? | |
| 104. The false omission rate of a test is 85%. | |
| We also know that the test's false positive rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 105. The false negative rate of a test is 85% and its false positive rate is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 106. The precision of a test is 85% and its sensitivity is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the negative predictive value of the test? | |
| 107. The false negative rate of a test is 90%. | |
| We also know that the test's specificity is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 108. The precision of a test is 90% and its false positive rate is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 109. The false discovery rate of a test is 95% and its specificity is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 110. The precision of a test is 95% and its sensitivity is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 111. The specificity of a test is 85%. | |
| We also know that the test's false negative rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 112. The false omission rate of a test is 90%. | |
| We also know that the test's false positive rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 113. The precision of a test is 90%. | |
| We also know that the test's false negative rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 114. The precision of a test is 85%. | |
| We also know that the test's specificity is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 115. The sensitivity of a test is 90% and its negative predictive value is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 116. The false positive rate of a test is 90%. | |
| We also know that the test's false discovery rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 117. The sensitivity of a test is 95% and its negative predictive value is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 118. The precision of a test is 85% and its negative predictive value is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 119. The specificity of a test is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 120. The false discovery rate of a test is 85% and its sensitivity is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the false negative rate of the test? | |
| 121. The false negative rate of a test is 85% and its false discovery rate is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the negative predictive value of the test? | |
| 122. The false negative rate of a test is 90%. | |
| We also know that the test's precision is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 123. The false negative rate of a test is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 124. The precision of a test is 90%. | |
| We also know that the test's specificity is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 125. The false omission rate of a test is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 126. The false negative rate of a test is 85% and its false positive rate is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the specificity of the test? | |
| 127. The negative predictive value of a test is 85%. | |
| We also know that the test's precision is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 128. The negative predictive value of a test is 85% and its false negative rate is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 129. The precision of a test is 95%. | |
| We also know that the test's sensitivity is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 130. The specificity of a test is 85% and its false omission rate is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 131. The false discovery rate of a test is 90% and its false omission rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 132. The false negative rate of a test is 85% and its false positive rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 133. The false positive rate of a test is 90%. | |
| We also know that the test's false omission rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 134. The sensitivity of a test is 95%. | |
| We also know that the test's precision is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 135. The negative predictive value of a test is 90%. | |
| We also know that the test's false discovery rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 136. The false positive rate of a test is 85% and its false discovery rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the false omission rate of the test? | |
| 137. The sensitivity of a test is 95% and its negative predictive value is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 138. The specificity of a test is 95% and its negative predictive value is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 139. The false discovery rate of a test is 85% and its sensitivity is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the specificity of the test? | |
| 140. The false discovery rate of a test is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 141. The precision of a test is 85% and its false omission rate is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 142. The precision of a test is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 143. The sensitivity of a test is 90% and its negative predictive value is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the false discovery rate of the test? | |
| 144. The precision of a test is 90%. | |
| We also know that the test's sensitivity is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 145. The precision of a test is 95% and its false negative rate is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the negative predictive value of the test? | |
| 146. The precision of a test is 90% and its false positive rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the sensitivity of the test? | |
| 147. The false negative rate of a test is 95% and its negative predictive value is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 148. The false negative rate of a test is 90% and its specificity is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the false positive rate of the test? | |
| 149. The false negative rate of a test is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 150. The false discovery rate of a test is 85% and its false negative rate is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 151. The false positive rate of a test is 90% and its false negative rate is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 152. The false discovery rate of a test is 85% and its false omission rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 153. The false discovery rate of a test is 95%. | |
| We also know that the test's sensitivity is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 154. The precision of a test is 85% and its false omission rate is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the false positive rate of the test? | |
| 155. The sensitivity of a test is 90%. | |
| We also know that the test's false omission rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 156. The negative predictive value of a test is 95%. | |
| We also know that the test's false negative rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 157. The sensitivity of a test is 90%. | |
| We also know that the test's specificity is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 158. The false positive rate of a test is 95% and its false negative rate is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the false omission rate of the test? | |
| 159. The precision of a test is 85% and its false positive rate is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 160. The precision of a test is 90%. | |
| We also know that the test's specificity is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 161. The false discovery rate of a test is 90%. | |
| We also know that the test's false positive rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 162. The false negative rate of a test is 85% and its false omission rate is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the specificity of the test? | |
| 163. The negative predictive value of a test is 90%. | |
| We also know that the test's false positive rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 164. The false negative rate of a test is 90%. | |
| We also know that the test's false omission rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 165. The negative predictive value of a test is 90% and its false positive rate is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 166. The false negative rate of a test is 90%. | |
| We also know that the test's false positive rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 167. The negative predictive value of a test is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 168. The false negative rate of a test is 95% and its false discovery rate is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the false omission rate of the test? | |
| 169. The precision of a test is 95% and its sensitivity is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 170. The precision of a test is 90% and its false negative rate is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 171. The false negative rate of a test is 85%. | |
| We also know that the test's false omission rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 172. The false positive rate of a test is 85%. | |
| We also know that the test's sensitivity is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 173. The sensitivity of a test is 85% and its false positive rate is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the false discovery rate of the test? | |
| 174. The negative predictive value of a test is 95%. | |
| We also know that the test's false discovery rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 175. The false discovery rate of a test is 95% and its sensitivity is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 176. The specificity of a test is 95% and its false negative rate is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 177. The specificity of a test is 85% and its sensitivity is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the false discovery rate of the test? | |
| 178. The false omission rate of a test is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 179. The specificity of a test is 90% and its false omission rate is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the sensitivity of the test? | |
| 180. The negative predictive value of a test is 85%. | |
| We also know that the test's specificity is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 181. The false omission rate of a test is 90% and its sensitivity is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the precision of the test? | |
| 182. The false omission rate of a test is 95% and its specificity is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the false negative rate of the test? | |
| 183. The sensitivity of a test is 85% and its precision is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 184. The false positive rate of a test is 90% and its precision is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the false discovery rate of the test? | |
| 185. The false positive rate of a test is 95% and its false negative rate is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the false omission rate of the test? | |
| 186. The precision of a test is 85% and its negative predictive value is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the false negative rate of the test? | |
| 187. The precision of a test is 95%. | |
| We also know that the test's false positive rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 188. The false negative rate of a test is 95%. | |
| We also know that the test's false omission rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 189. The false negative rate of a test is 95%. | |
| We also know that the test's false positive rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 190. The precision of a test is 85%. | |
| We also know that the test's specificity is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 191. The sensitivity of a test is 85%. | |
| We also know that the test's false positive rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 192. The false positive rate of a test is 95% and its negative predictive value is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 193. The false negative rate of a test is 85%. | |
| We also know that the test's precision is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 194. The false negative rate of a test is 85%. | |
| We also know that the test's negative predictive value is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 195. The sensitivity of a test is 85% and its specificity is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 196. The specificity of a test is 95% and its negative predictive value is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the false omission rate of the test? | |
| 197. The false omission rate of a test is 90% and its precision is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 198. The false discovery rate of a test is 90% and its negative predictive value is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the sensitivity of the test? | |
| 199. The specificity of a test is 90% and its false negative rate is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the negative predictive value of the test? | |
| 200. The negative predictive value of a test is 90% and its precision is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the sensitivity of the test? | |
| 201. The false discovery rate of a test is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 202. The precision of a test is 85% and its specificity is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the false positive rate of the test? | |
| 203. The specificity of a test is 90%. | |
| We also know that the test's negative predictive value is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 204. The specificity of a test is 85% and its negative predictive value is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 205. The precision of a test is 95% and its negative predictive value is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 206. The negative predictive value of a test is 85% and its specificity is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 207. The false negative rate of a test is 85%. | |
| We also know that the test's false omission rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 208. The negative predictive value of a test is 90% and its specificity is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 209. The negative predictive value of a test is 85% and its false discovery rate is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 210. The sensitivity of a test is 90%. | |
| We also know that the test's precision is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 211. The false positive rate of a test is 90% and its false omission rate is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the false discovery rate of the test? | |
| 212. The precision of a test is 85% and its false positive rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the specificity of the test? | |
| 213. The specificity of a test is 85%. | |
| We also know that the test's false negative rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 214. The false discovery rate of a test is 85%. | |
| We also know that the test's sensitivity is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 215. The specificity of a test is 95%. | |
| We also know that the test's sensitivity is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 216. The false positive rate of a test is 85% and its false omission rate is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 217. The specificity of a test is 90%. | |
| We also know that the test's false discovery rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 218. The precision of a test is 85% and its specificity is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 219. The false discovery rate of a test is 90%. | |
| We also know that the test's false negative rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 220. The false negative rate of a test is 95% and its false discovery rate is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the precision of the test? | |
| 221. The sensitivity of a test is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 222. The sensitivity of a test is 95%. | |
| We also know that the test's false positive rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 223. The false negative rate of a test is 90% and its false positive rate is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 224. The precision of a test is 85%. | |
| We also know that the test's negative predictive value is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 225. The false omission rate of a test is 85% and its false positive rate is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the false discovery rate of the test? | |
| 226. The false negative rate of a test is 95%. | |
| We also know that the test's false omission rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 227. The precision of a test is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 228. The false negative rate of a test is 85% and its precision is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 229. The sensitivity of a test is 85% and its false omission rate is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the false positive rate of the test? | |
| 230. The false discovery rate of a test is 95%. | |
| We also know that the test's sensitivity is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 231. The false positive rate of a test is 90%. | |
| We also know that the test's false discovery rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 232. The false negative rate of a test is 85% and its negative predictive value is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 233. The false omission rate of a test is 90%. | |
| We also know that the test's false negative rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 234. The sensitivity of a test is 95% and its precision is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the false positive rate of the test? | |
| 235. The false positive rate of a test is 95%. | |
| We also know that the test's negative predictive value is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 236. The false negative rate of a test is 85%. | |
| We also know that the test's negative predictive value is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 237. The false omission rate of a test is 90% and its sensitivity is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the specificity of the test? | |
| 238. The false discovery rate of a test is 85% and its false omission rate is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the negative predictive value of the test? | |
| 239. The false positive rate of a test is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 240. The negative predictive value of a test is 90%. | |
| We also know that the test's false discovery rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 241. The false discovery rate of a test is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 242. The sensitivity of a test is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 243. The negative predictive value of a test is 85% and its false discovery rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 244. The false negative rate of a test is 90% and its negative predictive value is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 245. The false omission rate of a test is 90% and its specificity is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the false discovery rate of the test? | |
| 246. The false positive rate of a test is 90%. | |
| We also know that the test's precision is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 247. The false positive rate of a test is 85%. | |
| We also know that the test's sensitivity is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 248. The specificity of a test is 95% and its false omission rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the precision of the test? | |
| 249. The negative predictive value of a test is 90%. | |
| We also know that the test's specificity is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 250. The precision of a test is 85% and its sensitivity is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the specificity of the test? | |
| 251. The false omission rate of a test is 95% and its sensitivity is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 252. The negative predictive value of a test is 90%. | |
| We also know that the test's specificity is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 253. The specificity of a test is 85% and its sensitivity is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the false negative rate of the test? | |
| 254. The precision of a test is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 255. The specificity of a test is 85% and its sensitivity is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 256. The sensitivity of a test is 90% and its precision is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 257. The false omission rate of a test is 90% and its false positive rate is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the specificity of the test? | |
| 258. The false discovery rate of a test is 90% and its false negative rate is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the false positive rate of the test? | |
| 259. The specificity of a test is 95%. | |
| We also know that the test's precision is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 260. The specificity of a test is 95%. | |
| We also know that the test's false omission rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 261. The negative predictive value of a test is 85%. | |
| We also know that the test's false discovery rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 262. The false positive rate of a test is 95%. | |
| We also know that the test's sensitivity is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 263. The negative predictive value of a test is 85% and its false discovery rate is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the false positive rate of the test? | |
| 264. The precision of a test is 85% and its false positive rate is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 265. The false positive rate of a test is 95% and its sensitivity is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the negative predictive value of the test? | |
| 266. The precision of a test is 85% and its false negative rate is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the negative predictive value of the test? | |
| 267. The specificity of a test is 95% and its negative predictive value is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 268. The sensitivity of a test is 85% and its false omission rate is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 269. The negative predictive value of a test is 95%. | |
| We also know that the test's false positive rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 270. The false omission rate of a test is 85% and its specificity is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the precision of the test? | |
| 271. The precision of a test is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 272. The false discovery rate of a test is 95% and its false positive rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 273. The precision of a test is 85% and its false negative rate is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the sensitivity of the test? | |
| 274. The false positive rate of a test is 90%. | |
| We also know that the test's false omission rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 275. The precision of a test is 95%. | |
| We also know that the test's negative predictive value is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 276. The false discovery rate of a test is 85% and its false negative rate is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 277. The false omission rate of a test is 85% and its false negative rate is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the false discovery rate of the test? | |
| 278. The false omission rate of a test is 90% and its sensitivity is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 279. The precision of a test is 95% and its false omission rate is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 280. The false negative rate of a test is 85% and its false discovery rate is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 281. The false negative rate of a test is 90%. | |
| We also know that the test's false omission rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 282. The sensitivity of a test is 85% and its false positive rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the negative predictive value of the test? | |
| 283. The sensitivity of a test is 90% and its false omission rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the specificity of the test? | |
| 284. The negative predictive value of a test is 85% and its specificity is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 285. The sensitivity of a test is 90% and its specificity is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 286. The false omission rate of a test is 90% and its false positive rate is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 287. The false positive rate of a test is 85%. | |
| We also know that the test's sensitivity is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 288. The specificity of a test is 95% and its false omission rate is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the false discovery rate of the test? | |
| 289. The negative predictive value of a test is 90% and its false negative rate is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the precision of the test? | |
| 290. The sensitivity of a test is 90%. | |
| We also know that the test's precision is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 291. The false discovery rate of a test is 95% and its false positive rate is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the false negative rate of the test? | |
| 292. The precision of a test is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 293. The precision of a test is 85% and its sensitivity is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 294. The sensitivity of a test is 95% and its false positive rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 295. The false positive rate of a test is 95% and its false discovery rate is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 296. The false discovery rate of a test is 85% and its sensitivity is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 297. The false omission rate of a test is 95%. | |
| We also know that the test's false positive rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 298. The false positive rate of a test is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 299. The negative predictive value of a test is 95% and its false positive rate is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 300. The sensitivity of a test is 85% and its false discovery rate is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the negative predictive value of the test? | |
| 301. The negative predictive value of a test is 90%. | |
| We also know that the test's precision is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 302. The specificity of a test is 95% and its false negative rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 303. The false omission rate of a test is 95%. | |
| We also know that the test's false negative rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 304. The false discovery rate of a test is 90%. | |
| We also know that the test's false omission rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 305. The negative predictive value of a test is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 306. The negative predictive value of a test is 90% and its false negative rate is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 307. The specificity of a test is 85%. | |
| We also know that the test's false discovery rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 308. The negative predictive value of a test is 85% and its false positive rate is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the specificity of the test? | |
| 309. The precision of a test is 85%. | |
| We also know that the test's false positive rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 310. The false positive rate of a test is 90% and its precision is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the negative predictive value of the test? | |
| 311. The false discovery rate of a test is 85% and its sensitivity is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the false negative rate of the test? | |
| 312. The false negative rate of a test is 85%. | |
| We also know that the test's false positive rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 313. The negative predictive value of a test is 95% and its false discovery rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the false negative rate of the test? | |
| 314. The precision of a test is 95% and its false negative rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 315. The specificity of a test is 90%. | |
| We also know that the test's false negative rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 316. The specificity of a test is 95%. | |
| We also know that the test's negative predictive value is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 317. The false positive rate of a test is 90%. | |
| We also know that the test's false negative rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 318. The specificity of a test is 90%. | |
| We also know that the test's negative predictive value is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 319. The specificity of a test is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 320. The false discovery rate of a test is 95%. | |
| We also know that the test's negative predictive value is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 321. The false positive rate of a test is 85% and its sensitivity is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the false omission rate of the test? | |
| 322. The precision of a test is 95% and its specificity is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 323. The precision of a test is 90% and its sensitivity is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the false omission rate of the test? | |
| 324. The false discovery rate of a test is 90%. | |
| We also know that the test's false negative rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 325. The false negative rate of a test is 95% and its false discovery rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 326. The specificity of a test is 85% and its false negative rate is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the precision of the test? | |
| 327. The false positive rate of a test is 90% and its false discovery rate is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 328. The false positive rate of a test is 90% and its false omission rate is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 329. The false negative rate of a test is 85%. | |
| We also know that the test's negative predictive value is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 330. The negative predictive value of a test is 85% and its specificity is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the sensitivity of the test? | |
| 331. The sensitivity of a test is 85%. | |
| We also know that the test's false positive rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 332. The precision of a test is 95% and its specificity is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 333. The specificity of a test is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 334. The precision of a test is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 335. The false positive rate of a test is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 336. The false omission rate of a test is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 337. The false discovery rate of a test is 95% and its sensitivity is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the false negative rate of the test? | |
| 338. The false discovery rate of a test is 90% and its negative predictive value is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 339. The specificity of a test is 95% and its false negative rate is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 340. The specificity of a test is 85% and its false omission rate is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 341. The false positive rate of a test is 90%. | |
| We also know that the test's false negative rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 342. The false negative rate of a test is 90% and its specificity is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 343. The false discovery rate of a test is 95%. | |
| We also know that the test's false positive rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 344. The false positive rate of a test is 85% and its precision is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 345. The sensitivity of a test is 85%. | |
| We also know that the test's specificity is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 346. The false omission rate of a test is 85% and its false positive rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 347. The negative predictive value of a test is 85% and its specificity is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the false discovery rate of the test? | |
| 348. The specificity of a test is 95%. | |
| We also know that the test's false negative rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 349. The false negative rate of a test is 90%. | |
| We also know that the test's false positive rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 350. The false discovery rate of a test is 90% and its false negative rate is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the negative predictive value of the test? | |
| 351. The specificity of a test is 85%. | |
| We also know that the test's false omission rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 352. The negative predictive value of a test is 95%. | |
| We also know that the test's sensitivity is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 353. The specificity of a test is 95% and its false negative rate is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 354. The specificity of a test is 90%. | |
| We also know that the test's negative predictive value is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 355. The false discovery rate of a test is 95% and its false positive rate is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 356. The precision of a test is 95%. | |
| We also know that the test's false omission rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 357. The false negative rate of a test is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 358. The false positive rate of a test is 85% and its false omission rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 359. The sensitivity of a test is 90% and its false positive rate is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the negative predictive value of the test? | |
| 360. The false negative rate of a test is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 361. The false negative rate of a test is 95%. | |
| We also know that the test's false positive rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 362. The negative predictive value of a test is 95%. | |
| We also know that the test's specificity is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 363. The false discovery rate of a test is 90%. | |
| We also know that the test's false positive rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 364. The false omission rate of a test is 90% and its sensitivity is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 365. The negative predictive value of a test is 95%. | |
| We also know that the test's sensitivity is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 366. The false positive rate of a test is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 367. The specificity of a test is 90% and its precision is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 368. The false negative rate of a test is 90% and its negative predictive value is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 369. The precision of a test is 90% and its sensitivity is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the false negative rate of the test? | |
| 370. The negative predictive value of a test is 95% and its false positive rate is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 371. The sensitivity of a test is 85% and its precision is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 372. The specificity of a test is 85% and its sensitivity is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the false discovery rate of the test? | |
| 373. The specificity of a test is 95%. | |
| We also know that the test's negative predictive value is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 374. The specificity of a test is 95% and its precision is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 375. The false discovery rate of a test is 90% and its sensitivity is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 376. The specificity of a test is 90%. | |
| We also know that the test's false omission rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 377. The false omission rate of a test is 90%. | |
| We also know that the test's false discovery rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 378. The false discovery rate of a test is 85%. | |
| We also know that the test's false positive rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 379. The sensitivity of a test is 90%. | |
| We also know that the test's false omission rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 380. The false discovery rate of a test is 95% and its false omission rate is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the false positive rate of the test? | |
| 381. The false positive rate of a test is 90% and its sensitivity is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the false omission rate of the test? | |
| 382. The sensitivity of a test is 90%. | |
| We also know that the test's negative predictive value is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 383. The false omission rate of a test is 90% and its specificity is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 384. The precision of a test is 90%. | |
| We also know that the test's false omission rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 385. The specificity of a test is 95% and its precision is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the negative predictive value of the test? | |
| 386. The negative predictive value of a test is 90% and its false discovery rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the sensitivity of the test? | |
| 387. The precision of a test is 90%. | |
| We also know that the test's negative predictive value is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 388. The false omission rate of a test is 90% and its false negative rate is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the specificity of the test? | |
| 389. The false positive rate of a test is 90% and its sensitivity is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the false discovery rate of the test? | |
| 390. The negative predictive value of a test is 85% and its false discovery rate is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 391. The sensitivity of a test is 85% and its false omission rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 392. The sensitivity of a test is 85% and its specificity is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 393. The false positive rate of a test is 90%. | |
| We also know that the test's negative predictive value is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 394. The sensitivity of a test is 95% and its negative predictive value is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 395. The false discovery rate of a test is 95% and its false negative rate is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the specificity of the test? | |
| 396. The negative predictive value of a test is 95% and its specificity is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 397. The specificity of a test is 95%. | |
| We also know that the test's sensitivity is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 398. The specificity of a test is 85% and its sensitivity is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 399. The false discovery rate of a test is 90% and its false omission rate is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the negative predictive value of the test? | |
| 400. The precision of a test is 85% and its specificity is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the false omission rate of the test? | |
| 401. The specificity of a test is 95%. | |
| We also know that the test's false negative rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 402. The specificity of a test is 85% and its negative predictive value is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the precision of the test? | |
| 403. The specificity of a test is 90% and its false discovery rate is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the false negative rate of the test? | |
| 404. The sensitivity of a test is 85% and its negative predictive value is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 405. The negative predictive value of a test is 85%. | |
| We also know that the test's false negative rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 406. The sensitivity of a test is 85%. | |
| We also know that the test's false omission rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 407. The specificity of a test is 95% and its false omission rate is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the precision of the test? | |
| 408. The false omission rate of a test is 85% and its false negative rate is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the specificity of the test? | |
| 409. The false omission rate of a test is 95% and its sensitivity is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the false positive rate of the test? | |
| 410. The false discovery rate of a test is 85% and its false positive rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the false negative rate of the test? | |
| 411. The false positive rate of a test is 85% and its false omission rate is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 412. The precision of a test is 85% and its sensitivity is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the false negative rate of the test? | |
| 413. The false omission rate of a test is 95% and its false discovery rate is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the false negative rate of the test? | |
| 414. The false omission rate of a test is 85%. | |
| We also know that the test's false negative rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 415. The negative predictive value of a test is 85% and its false positive rate is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 416. The specificity of a test is 95% and its sensitivity is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 417. The specificity of a test is 95% and its precision is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the negative predictive value of the test? | |
| 418. The precision of a test is 95% and its negative predictive value is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 419. The precision of a test is 90% and its specificity is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 420. The false discovery rate of a test is 95% and its false positive rate is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the false negative rate of the test? | |
| 421. The false positive rate of a test is 90%. | |
| We also know that the test's false omission rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 422. The false negative rate of a test is 85%. | |
| We also know that the test's false omission rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 423. The false discovery rate of a test is 95% and its negative predictive value is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the specificity of the test? | |
| 424. The false omission rate of a test is 95% and its sensitivity is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 425. The sensitivity of a test is 85% and its false positive rate is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 426. The false omission rate of a test is 90% and its false discovery rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 427. The false discovery rate of a test is 90%. | |
| We also know that the test's false omission rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 428. The sensitivity of a test is 95% and its negative predictive value is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the false discovery rate of the test? | |
| 429. The false omission rate of a test is 85% and its false discovery rate is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 430. The false negative rate of a test is 85% and its false positive rate is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the false discovery rate of the test? | |
| 431. The precision of a test is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 432. The sensitivity of a test is 85%. | |
| We also know that the test's specificity is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 433. The false positive rate of a test is 90% and its negative predictive value is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the false omission rate of the test? | |
| 434. The specificity of a test is 95% and its false negative rate is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 435. The sensitivity of a test is 95%. | |
| We also know that the test's precision is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 436. The false omission rate of a test is 95% and its false positive rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the false discovery rate of the test? | |
| 437. The false discovery rate of a test is 90% and its sensitivity is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 438. The sensitivity of a test is 95%. | |
| We also know that the test's false positive rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 439. The precision of a test is 95% and its sensitivity is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the negative predictive value of the test? | |
| 440. The false discovery rate of a test is 95%. | |
| We also know that the test's false negative rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 441. The false negative rate of a test is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 442. The false omission rate of a test is 85% and its precision is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 443. The false omission rate of a test is 95% and its sensitivity is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 444. The sensitivity of a test is 95%. | |
| We also know that the test's specificity is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 445. The precision of a test is 90% and its sensitivity is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 446. The negative predictive value of a test is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 447. The specificity of a test is 90%. | |
| We also know that the test's false omission rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 448. The false omission rate of a test is 90% and its false discovery rate is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 449. The precision of a test is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 450. The false negative rate of a test is 95%. | |
| We also know that the test's false discovery rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 451. The negative predictive value of a test is 90% and its specificity is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the false positive rate of the test? | |
| 452. The precision of a test is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 453. The false positive rate of a test is 85%. | |
| We also know that the test's sensitivity is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 454. The specificity of a test is 90% and its false negative rate is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the false discovery rate of the test? | |
| 455. The sensitivity of a test is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 456. The specificity of a test is 90%. | |
| We also know that the test's precision is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 457. The specificity of a test is 85%. | |
| We also know that the test's false discovery rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 458. The false negative rate of a test is 85% and its false discovery rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 459. The sensitivity of a test is 95% and its false positive rate is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the false omission rate of the test? | |
| 460. The specificity of a test is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 461. The false discovery rate of a test is 90% and its specificity is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 462. The negative predictive value of a test is 85% and its sensitivity is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the false discovery rate of the test? | |
| 463. The false omission rate of a test is 95%. | |
| We also know that the test's false discovery rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 464. The specificity of a test is 85% and its negative predictive value is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 465. The false negative rate of a test is 95% and its false omission rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the false discovery rate of the test? | |
| 466. The false negative rate of a test is 95% and its precision is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 467. The negative predictive value of a test is 85% and its false negative rate is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 468. The false positive rate of a test is 90% and its negative predictive value is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the false negative rate of the test? | |
| 469. The false positive rate of a test is 90%. | |
| We also know that the test's false omission rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 470. The false negative rate of a test is 90% and its false omission rate is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the false discovery rate of the test? | |
| 471. The false negative rate of a test is 90% and its precision is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 472. The false discovery rate of a test is 90% and its false positive rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the negative predictive value of the test? | |
| 473. The false omission rate of a test is 90%. | |
| We also know that the test's precision is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 474. The false negative rate of a test is 95%. | |
| We also know that the test's false discovery rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 475. The false negative rate of a test is 90% and its negative predictive value is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the false positive rate of the test? | |
| 476. The false negative rate of a test is 85% and its negative predictive value is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 477. The false positive rate of a test is 90% and its precision is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the false omission rate of the test? | |
| 478. The false positive rate of a test is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 479. The precision of a test is 95% and its negative predictive value is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 480. The false negative rate of a test is 95% and its negative predictive value is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the precision of the test? | |
| 481. The false negative rate of a test is 90% and its precision is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the false omission rate of the test? | |
| 482. The false positive rate of a test is 90% and its sensitivity is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 483. The sensitivity of a test is 95%. | |
| We also know that the test's false positive rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 484. The false negative rate of a test is 90% and its false omission rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 485. The precision of a test is 95% and its false negative rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the specificity of the test? | |
| 486. The false negative rate of a test is 85% and its specificity is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 487. The false negative rate of a test is 90% and its false discovery rate is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the negative predictive value of the test? | |
| 488. The precision of a test is 95%. | |
| We also know that the test's false omission rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 489. The specificity of a test is 90%. | |
| We also know that the test's false omission rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 490. The precision of a test is 85%. | |
| We also know that the test's sensitivity is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 491. The false omission rate of a test is 90% and its sensitivity is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the false discovery rate of the test? | |
| 492. The sensitivity of a test is 95% and its false positive rate is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 493. The specificity of a test is 85% and its precision is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the false negative rate of the test? | |
| 494. The false negative rate of a test is 95% and its false discovery rate is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 495. The sensitivity of a test is 90% and its false discovery rate is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the specificity of the test? | |
| 496. The precision of a test is 95% and its specificity is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the false positive rate of the test? | |
| 497. The precision of a test is 95% and its negative predictive value is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the false positive rate of the test? | |
| 498. The false omission rate of a test is 85% and its false negative rate is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 499. The false omission rate of a test is 90% and its specificity is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the precision of the test? | |
| 500. The negative predictive value of a test is 90% and its sensitivity is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 501. The precision of a test is 90%. | |
| We also know that the test's false omission rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 502. The negative predictive value of a test is 85%. | |
| We also know that the test's false positive rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 503. The negative predictive value of a test is 85% and its precision is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the false negative rate of the test? | |
| 504. The false discovery rate of a test is 90% and its specificity is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the negative predictive value of the test? | |
| 505. The precision of a test is 85% and its sensitivity is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 506. The sensitivity of a test is 85%. | |
| We also know that the test's false omission rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 507. The false negative rate of a test is 85% and its precision is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 508. The precision of a test is 90%. | |
| We also know that the test's negative predictive value is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 509. The negative predictive value of a test is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 510. The specificity of a test is 95% and its sensitivity is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 511. The negative predictive value of a test is 95% and its specificity is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the precision of the test? | |
| 512. The specificity of a test is 95%. | |
| We also know that the test's false omission rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 513. The false omission rate of a test is 95% and its specificity is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the false negative rate of the test? | |
| 514. The precision of a test is 90% and its sensitivity is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 515. The false discovery rate of a test is 85% and its false positive rate is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the specificity of the test? | |
| 516. The precision of a test is 95% and its false negative rate is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the negative predictive value of the test? | |
| 517. The precision of a test is 85% and its sensitivity is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 518. The false discovery rate of a test is 95% and its sensitivity is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the false positive rate of the test? | |
| 519. The specificity of a test is 95% and its precision is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the false omission rate of the test? | |
| 520. The false positive rate of a test is 90% and its false negative rate is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 521. The false negative rate of a test is 95% and its false omission rate is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the specificity of the test? | |
| 522. The precision of a test is 90% and its false negative rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 523. The false negative rate of a test is 85% and its specificity is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the negative predictive value of the test? | |
| 524. The specificity of a test is 85% and its false omission rate is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 525. The sensitivity of a test is 85%. | |
| We also know that the test's false omission rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 526. The false positive rate of a test is 95%. | |
| We also know that the test's negative predictive value is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 527. The negative predictive value of a test is 85% and its specificity is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the false discovery rate of the test? | |
| 528. The false discovery rate of a test is 95% and its false negative rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 529. The specificity of a test is 90%. | |
| We also know that the test's sensitivity is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 530. The false negative rate of a test is 90% and its negative predictive value is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the false positive rate of the test? | |
| 531. The false omission rate of a test is 85%. | |
| We also know that the test's specificity is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 532. The negative predictive value of a test is 85% and its false positive rate is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the precision of the test? | |
| 533. The sensitivity of a test is 90% and its negative predictive value is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the false omission rate of the test? | |
| 534. The specificity of a test is 90% and its sensitivity is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 535. The false negative rate of a test is 85% and its specificity is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the false discovery rate of the test? | |
| 536. The precision of a test is 95% and its specificity is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the negative predictive value of the test? | |
| 537. The negative predictive value of a test is 90% and its false positive rate is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 538. The precision of a test is 95%. | |
| We also know that the test's false positive rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 539. The precision of a test is 95% and its false positive rate is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the false omission rate of the test? | |
| 540. The false negative rate of a test is 90%. | |
| We also know that the test's false omission rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 541. The specificity of a test is 90%. | |
| We also know that the test's negative predictive value is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 542. The false discovery rate of a test is 90% and its false negative rate is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 543. The negative predictive value of a test is 95% and its false positive rate is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the precision of the test? | |
| 544. The false omission rate of a test is 85% and its false positive rate is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 545. The negative predictive value of a test is 90% and its precision is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the specificity of the test? | |
| 546. The false discovery rate of a test is 85% and its negative predictive value is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 547. The negative predictive value of a test is 90% and its false negative rate is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 548. The precision of a test is 85% and its false omission rate is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the sensitivity of the test? | |
| 549. The sensitivity of a test is 85% and its negative predictive value is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the specificity of the test? | |
| 550. The false negative rate of a test is 90% and its precision is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 551. The false discovery rate of a test is 85% and its false omission rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the false positive rate of the test? | |
| 552. The false discovery rate of a test is 90% and its sensitivity is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the negative predictive value of the test? | |
| 553. The specificity of a test is 90% and its false omission rate is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 554. The precision of a test is 85% and its false omission rate is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the sensitivity of the test? | |
| 555. The negative predictive value of a test is 90% and its false positive rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 556. The false discovery rate of a test is 85%. | |
| We also know that the test's false omission rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 557. The false positive rate of a test is 95% and its false omission rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 558. The specificity of a test is 90% and its false omission rate is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the precision of the test? | |
| 559. The false positive rate of a test is 95% and its sensitivity is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the precision of the test? | |
| 560. The specificity of a test is 95% and its false discovery rate is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 561. The false discovery rate of a test is 95% and its negative predictive value is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the false positive rate of the test? | |
| 562. The sensitivity of a test is 95% and its negative predictive value is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the precision of the test? | |
| 563. The sensitivity of a test is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 564. The false omission rate of a test is 85% and its specificity is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 565. The false omission rate of a test is 85%. | |
| We also know that the test's sensitivity is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 566. The sensitivity of a test is 85% and its negative predictive value is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 567. The false positive rate of a test is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 568. The false negative rate of a test is 85% and its precision is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 569. The false omission rate of a test is 85% and its false negative rate is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 570. The false discovery rate of a test is 90%. | |
| We also know that the test's negative predictive value is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 571. The precision of a test is 85% and its false positive rate is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the specificity of the test? | |
| 572. The false discovery rate of a test is 95% and its specificity is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the negative predictive value of the test? | |
| 573. The negative predictive value of a test is 95% and its precision is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the specificity of the test? | |
| 574. The false discovery rate of a test is 90% and its sensitivity is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the negative predictive value of the test? | |
| 575. The false discovery rate of a test is 90% and its false positive rate is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 576. The false omission rate of a test is 95% and its false negative rate is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 577. The specificity of a test is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 578. The false positive rate of a test is 90% and its false omission rate is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 579. The negative predictive value of a test is 85% and its sensitivity is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the false discovery rate of the test? | |
| 580. The negative predictive value of a test is 90% and its false negative rate is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 581. The precision of a test is 95% and its sensitivity is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 582. The false positive rate of a test is 90% and its false negative rate is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the negative predictive value of the test? | |
| 583. The negative predictive value of a test is 85% and its sensitivity is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the precision of the test? | |
| 584. The sensitivity of a test is 85% and its false positive rate is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 585. The sensitivity of a test is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 586. The false discovery rate of a test is 85%. | |
| We also know that the test's specificity is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 587. The sensitivity of a test is 95% and its false omission rate is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 588. The specificity of a test is 85%. | |
| We also know that the test's negative predictive value is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 589. The precision of a test is 95% and its sensitivity is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 590. The precision of a test is 90% and its false negative rate is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 591. The sensitivity of a test is 90% and its specificity is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the negative predictive value of the test? | |
| 592. The precision of a test is 90% and its negative predictive value is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 593. The sensitivity of a test is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 594. The precision of a test is 90%. | |
| We also know that the test's specificity is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 595. The precision of a test is 85% and its sensitivity is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 596. The false omission rate of a test is 95%. | |
| We also know that the test's false positive rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 597. The false discovery rate of a test is 95%. | |
| We also know that the test's sensitivity is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 598. The false negative rate of a test is 95% and its false discovery rate is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the false omission rate of the test? | |
| 599. The specificity of a test is 95% and its precision is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 600. The false omission rate of a test is 95% and its false negative rate is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the false discovery rate of the test? | |
| 601. The specificity of a test is 90%. | |
| We also know that the test's false discovery rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 602. The specificity of a test is 95%. | |
| We also know that the test's sensitivity is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 603. The sensitivity of a test is 95% and its false positive rate is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the precision of the test? | |
| 604. The false omission rate of a test is 85% and its false negative rate is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 605. The sensitivity of a test is 95% and its precision is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 606. The false negative rate of a test is 90% and its precision is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the false omission rate of the test? | |
| 607. The precision of a test is 90% and its false omission rate is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 608. The precision of a test is 85% and its false negative rate is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the specificity of the test? | |
| 609. The false negative rate of a test is 90%. | |
| We also know that the test's negative predictive value is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 610. The sensitivity of a test is 85%. | |
| We also know that the test's negative predictive value is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 611. The precision of a test is 95% and its sensitivity is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the false positive rate of the test? | |
| 612. The false omission rate of a test is 90%. | |
| We also know that the test's false negative rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 613. The false discovery rate of a test is 95% and its negative predictive value is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 614. The specificity of a test is 90%. | |
| We also know that the test's false discovery rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 615. The false discovery rate of a test is 85% and its false negative rate is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 616. The false discovery rate of a test is 85% and its false positive rate is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 617. The false discovery rate of a test is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 618. The specificity of a test is 95%. | |
| We also know that the test's negative predictive value is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 619. The specificity of a test is 90% and its false discovery rate is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 620. The false discovery rate of a test is 85% and its false negative rate is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the false omission rate of the test? | |
| 621. The specificity of a test is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 622. The false negative rate of a test is 90% and its negative predictive value is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 623. The false positive rate of a test is 95%. | |
| We also know that the test's false negative rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 624. The specificity of a test is 95% and its negative predictive value is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 625. The false omission rate of a test is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 626. The false omission rate of a test is 95%. | |
| We also know that the test's precision is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 627. The negative predictive value of a test is 90% and its false positive rate is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 628. The false positive rate of a test is 95%. | |
| We also know that the test's negative predictive value is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 629. The negative predictive value of a test is 95% and its specificity is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the precision of the test? | |
| 630. The negative predictive value of a test is 85% and its false discovery rate is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 631. The sensitivity of a test is 85%. | |
| We also know that the test's false positive rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 632. The false negative rate of a test is 85%. | |
| We also know that the test's precision is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 633. The negative predictive value of a test is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 634. The false discovery rate of a test is 85%. | |
| We also know that the test's sensitivity is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 635. The sensitivity of a test is 85% and its false positive rate is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 636. The false negative rate of a test is 90% and its false omission rate is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 637. The false positive rate of a test is 95% and its false omission rate is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the false discovery rate of the test? | |
| 638. The false omission rate of a test is 95%. | |
| We also know that the test's sensitivity is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 639. The sensitivity of a test is 95%. | |
| We also know that the test's precision is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 640. The false negative rate of a test is 95%. | |
| We also know that the test's false discovery rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 641. The specificity of a test is 90% and its false negative rate is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 642. The false positive rate of a test is 90% and its false discovery rate is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the false negative rate of the test? | |
| 643. The false omission rate of a test is 90% and its false negative rate is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 644. The false discovery rate of a test is 85% and its negative predictive value is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 645. The false discovery rate of a test is 90% and its false omission rate is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 646. The false discovery rate of a test is 85% and its false negative rate is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the specificity of the test? | |
| 647. The negative predictive value of a test is 90%. | |
| We also know that the test's false positive rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 648. The specificity of a test is 85% and its false discovery rate is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 649. The precision of a test is 95% and its negative predictive value is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 650. The false omission rate of a test is 90% and its false positive rate is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the sensitivity of the test? | |
| 651. The sensitivity of a test is 90%. | |
| We also know that the test's false positive rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 652. The false negative rate of a test is 85% and its precision is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the negative predictive value of the test? | |
| 653. The specificity of a test is 85%. | |
| We also know that the test's sensitivity is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 654. The negative predictive value of a test is 95% and its sensitivity is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the false discovery rate of the test? | |
| 655. The false negative rate of a test is 95% and its false discovery rate is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 656. The false negative rate of a test is 90%. | |
| We also know that the test's false discovery rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 657. The precision of a test is 85% and its sensitivity is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 658. The precision of a test is 85%. | |
| We also know that the test's negative predictive value is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 659. The false positive rate of a test is 90% and its false discovery rate is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 660. The specificity of a test is 95%. | |
| We also know that the test's false discovery rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 661. The specificity of a test is 95% and its false discovery rate is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 662. The precision of a test is 95%. | |
| We also know that the test's false omission rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 663. The false discovery rate of a test is 95% and its specificity is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the sensitivity of the test? | |
| 664. The specificity of a test is 85%. | |
| We also know that the test's false negative rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 665. The false negative rate of a test is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 666. The false discovery rate of a test is 85% and its false omission rate is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 667. The false omission rate of a test is 90% and its precision is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the specificity of the test? | |
| 668. The negative predictive value of a test is 90%. | |
| We also know that the test's sensitivity is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 669. The false negative rate of a test is 85% and its false omission rate is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the false positive rate of the test? | |
| 670. The sensitivity of a test is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 671. The specificity of a test is 95% and its false discovery rate is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 672. The false omission rate of a test is 95%. | |
| We also know that the test's specificity is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 673. The precision of a test is 85% and its false negative rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 674. The false negative rate of a test is 90% and its precision is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 675. The precision of a test is 95%. | |
| We also know that the test's false negative rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 676. The negative predictive value of a test is 90% and its false positive rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the false discovery rate of the test? | |
| 677. The false negative rate of a test is 85% and its false omission rate is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the false discovery rate of the test? | |
| 678. The false omission rate of a test is 95% and its false positive rate is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the precision of the test? | |
| 679. The false omission rate of a test is 85% and its false positive rate is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 680. The sensitivity of a test is 85% and its negative predictive value is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the precision of the test? | |
| 681. The precision of a test is 90% and its false negative rate is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the specificity of the test? | |
| 682. The false positive rate of a test is 90% and its false omission rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the precision of the test? | |
| 683. The negative predictive value of a test is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 684. The false omission rate of a test is 90%. | |
| We also know that the test's specificity is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 685. The false positive rate of a test is 85% and its sensitivity is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 686. The false discovery rate of a test is 90%. | |
| We also know that the test's false omission rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 687. The false discovery rate of a test is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 688. The false negative rate of a test is 95% and its false positive rate is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the false discovery rate of the test? | |
| 689. The false negative rate of a test is 90% and its precision is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 690. The false positive rate of a test is 85% and its false omission rate is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the false discovery rate of the test? | |
| 691. The false negative rate of a test is 85%. | |
| We also know that the test's false omission rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 692. The false positive rate of a test is 95% and its false negative rate is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the false omission rate of the test? | |
| 693. The false positive rate of a test is 90%. | |
| We also know that the test's negative predictive value is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 694. The sensitivity of a test is 95% and its false discovery rate is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 695. The negative predictive value of a test is 95% and its precision is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 696. The precision of a test is 90%. | |
| We also know that the test's false positive rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 697. The sensitivity of a test is 85%. | |
| We also know that the test's false discovery rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 698. The false positive rate of a test is 85% and its false negative rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the negative predictive value of the test? | |
| 699. The false discovery rate of a test is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 700. The false negative rate of a test is 95% and its false discovery rate is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the false omission rate of the test? | |
| 701. The negative predictive value of a test is 95% and its specificity is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the sensitivity of the test? | |
| 702. The sensitivity of a test is 95%. | |
| We also know that the test's specificity is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 703. The precision of a test is 95%. | |
| We also know that the test's negative predictive value is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 704. The false negative rate of a test is 95% and its negative predictive value is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 705. The specificity of a test is 85% and its false omission rate is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 706. The negative predictive value of a test is 85% and its precision is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 707. The false omission rate of a test is 90% and its sensitivity is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the precision of the test? | |
| 708. The false negative rate of a test is 90%. | |
| We also know that the test's specificity is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 709. The sensitivity of a test is 95% and its false positive rate is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 710. The false positive rate of a test is 90% and its sensitivity is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the false discovery rate of the test? | |
| 711. The false omission rate of a test is 95% and its specificity is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 712. The negative predictive value of a test is 90% and its specificity is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the precision of the test? | |
| 713. The precision of a test is 95% and its specificity is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 714. The false positive rate of a test is 95% and its sensitivity is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 715. The negative predictive value of a test is 85%. | |
| We also know that the test's precision is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 716. The negative predictive value of a test is 95%. | |
| We also know that the test's false discovery rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 717. The specificity of a test is 95%. | |
| We also know that the test's false omission rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 718. The false positive rate of a test is 85% and its false negative rate is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the negative predictive value of the test? | |
| 719. The false positive rate of a test is 90% and its false omission rate is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 720. The false discovery rate of a test is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 721. The sensitivity of a test is 90% and its false omission rate is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the specificity of the test? | |
| 722. The false omission rate of a test is 85% and its false negative rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 723. The sensitivity of a test is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 724. The false omission rate of a test is 95% and its false discovery rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 725. The specificity of a test is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 726. The sensitivity of a test is 85%. | |
| We also know that the test's false discovery rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 727. The specificity of a test is 85%. | |
| We also know that the test's false omission rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 728. The specificity of a test is 95% and its precision is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the sensitivity of the test? | |
| 729. The false negative rate of a test is 90% and its false discovery rate is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 730. The negative predictive value of a test is 90% and its precision is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the specificity of the test? | |
| 731. The specificity of a test is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 732. The sensitivity of a test is 90% and its negative predictive value is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the false discovery rate of the test? | |
| 733. The false omission rate of a test is 85% and its specificity is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 734. The false negative rate of a test is 95% and its false omission rate is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 735. The false negative rate of a test is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 736. The precision of a test is 90%. | |
| We also know that the test's false negative rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 737. The specificity of a test is 95%. | |
| We also know that the test's false negative rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 738. The sensitivity of a test is 95% and its specificity is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 739. The false positive rate of a test is 95% and its false negative rate is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 740. The false discovery rate of a test is 85%. | |
| We also know that the test's negative predictive value is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 741. The false discovery rate of a test is 85%. | |
| We also know that the test's false positive rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 742. The specificity of a test is 90% and its negative predictive value is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 743. The negative predictive value of a test is 90% and its false positive rate is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the precision of the test? | |
| 744. The sensitivity of a test is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 745. The specificity of a test is 85% and its sensitivity is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 746. The false negative rate of a test is 85% and its specificity is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 747. The negative predictive value of a test is 85%. | |
| We also know that the test's false discovery rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 748. The false discovery rate of a test is 85%. | |
| We also know that the test's false positive rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 749. The false negative rate of a test is 85%. | |
| We also know that the test's false positive rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 750. The false positive rate of a test is 95%. | |
| We also know that the test's sensitivity is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 751. The specificity of a test is 90% and its false negative rate is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the false omission rate of the test? | |
| 752. The false positive rate of a test is 90% and its negative predictive value is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the false discovery rate of the test? | |
| 753. The sensitivity of a test is 95% and its false discovery rate is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 754. The false omission rate of a test is 95% and its sensitivity is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 755. The false positive rate of a test is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 756. The specificity of a test is 95% and its negative predictive value is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the precision of the test? | |
| 757. The false negative rate of a test is 95%. | |
| We also know that the test's false positive rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 758. The negative predictive value of a test is 85%. | |
| We also know that the test's false positive rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 759. The specificity of a test is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 760. The false positive rate of a test is 85% and its sensitivity is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 761. The false negative rate of a test is 85%. | |
| We also know that the test's false discovery rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 762. The precision of a test is 90%. | |
| We also know that the test's specificity is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 763. The false omission rate of a test is 90%. | |
| We also know that the test's false positive rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 764. The specificity of a test is 90%. | |
| We also know that the test's sensitivity is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 765. The false negative rate of a test is 85% and its precision is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 766. The precision of a test is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 767. The sensitivity of a test is 85% and its false omission rate is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the precision of the test? | |
| 768. The negative predictive value of a test is 90% and its false negative rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 769. The false negative rate of a test is 95% and its false omission rate is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the false discovery rate of the test? | |
| 770. The precision of a test is 85% and its specificity is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the sensitivity of the test? | |
| 771. The false omission rate of a test is 85% and its sensitivity is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 772. The false discovery rate of a test is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 773. The sensitivity of a test is 85%. | |
| We also know that the test's negative predictive value is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 774. The false discovery rate of a test is 95% and its false positive rate is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the sensitivity of the test? | |
| 775. The negative predictive value of a test is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 776. The false omission rate of a test is 85%. | |
| We also know that the test's false positive rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 777. The precision of a test is 90% and its negative predictive value is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 778. The false negative rate of a test is 85% and its precision is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the specificity of the test? | |
| 779. The negative predictive value of a test is 90% and its precision is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the false discovery rate of the test? | |
| 780. The false negative rate of a test is 85% and its false discovery rate is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 781. The false negative rate of a test is 85% and its false omission rate is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 782. The false discovery rate of a test is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 783. The false positive rate of a test is 85%. | |
| We also know that the test's precision is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 784. The false omission rate of a test is 85% and its false positive rate is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the sensitivity of the test? | |
| 785. The false omission rate of a test is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 786. The sensitivity of a test is 90% and its precision is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 787. The false positive rate of a test is 85% and its false negative rate is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the negative predictive value of the test? | |
| 788. The false omission rate of a test is 90%. | |
| We also know that the test's precision is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 789. The false omission rate of a test is 95% and its specificity is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the precision of the test? | |
| 790. The precision of a test is 90% and its specificity is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the false negative rate of the test? | |
| 791. The false positive rate of a test is 90%. | |
| We also know that the test's false discovery rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 792. The precision of a test is 90%. | |
| We also know that the test's false omission rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 793. The false negative rate of a test is 95% and its false omission rate is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the specificity of the test? | |
| 794. The false positive rate of a test is 90% and its false discovery rate is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the false omission rate of the test? | |
| 795. The false negative rate of a test is 90%. | |
| We also know that the test's specificity is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 796. The false discovery rate of a test is 90% and its false negative rate is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the false positive rate of the test? | |
| 797. The specificity of a test is 85%. | |
| We also know that the test's false omission rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 798. The false negative rate of a test is 95%. | |
| We also know that the test's negative predictive value is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 799. The sensitivity of a test is 90%. | |
| We also know that the test's false discovery rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 800. The specificity of a test is 95% and its precision is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 801. The negative predictive value of a test is 95%. | |
| We also know that the test's specificity is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 802. The false negative rate of a test is 90% and its false positive rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the false discovery rate of the test? | |
| 803. The false discovery rate of a test is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 804. The sensitivity of a test is 95% and its specificity is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the negative predictive value of the test? | |
| 805. The false discovery rate of a test is 90% and its false positive rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the false omission rate of the test? | |
| 806. The sensitivity of a test is 85%. | |
| We also know that the test's false omission rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 807. The negative predictive value of a test is 85%. | |
| We also know that the test's false positive rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 808. The precision of a test is 90% and its false positive rate is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 809. The sensitivity of a test is 85% and its false omission rate is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the false discovery rate of the test? | |
| 810. The negative predictive value of a test is 95%. | |
| We also know that the test's false discovery rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 811. The false positive rate of a test is 90% and its false omission rate is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the negative predictive value of the test? | |
| 812. The false negative rate of a test is 85% and its negative predictive value is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 813. The false negative rate of a test is 95%. | |
| We also know that the test's false positive rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 814. The sensitivity of a test is 95% and its negative predictive value is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the false positive rate of the test? | |
| 815. The negative predictive value of a test is 95% and its false positive rate is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the precision of the test? | |
| 816. The false omission rate of a test is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 817. The false discovery rate of a test is 95% and its false positive rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 818. The false discovery rate of a test is 90%. | |
| We also know that the test's false positive rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 819. The negative predictive value of a test is 90% and its precision is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 820. The specificity of a test is 90% and its negative predictive value is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the false omission rate of the test? | |
| 821. The false negative rate of a test is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 822. The precision of a test is 85%. | |
| We also know that the test's specificity is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 823. The false positive rate of a test is 95% and its false discovery rate is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 824. The false discovery rate of a test is 85% and its false omission rate is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 825. The false omission rate of a test is 85% and its sensitivity is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the precision of the test? | |
| 826. The false positive rate of a test is 90% and its false omission rate is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the precision of the test? | |
| 827. The precision of a test is 85% and its negative predictive value is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the false negative rate of the test? | |
| 828. The negative predictive value of a test is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 829. The specificity of a test is 95%. | |
| We also know that the test's false omission rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 830. The false omission rate of a test is 85% and its false discovery rate is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the specificity of the test? | |
| 831. The false omission rate of a test is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 832. The negative predictive value of a test is 90%. | |
| We also know that the test's precision is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 833. The false omission rate of a test is 85% and its false positive rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the false negative rate of the test? | |
| 834. The false negative rate of a test is 85% and its negative predictive value is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 835. The sensitivity of a test is 90% and its false positive rate is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the negative predictive value of the test? | |
| 836. The specificity of a test is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 837. The false positive rate of a test is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 838. The false positive rate of a test is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 839. The false omission rate of a test is 90% and its false negative rate is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the specificity of the test? | |
| 840. The false omission rate of a test is 90% and its false positive rate is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 841. The false omission rate of a test is 90% and its false negative rate is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the false positive rate of the test? | |
| 842. The false negative rate of a test is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 843. The false positive rate of a test is 95% and its false discovery rate is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 844. The false discovery rate of a test is 85% and its false omission rate is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the false negative rate of the test? | |
| 845. The false negative rate of a test is 85%. | |
| We also know that the test's false omission rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 846. The negative predictive value of a test is 90%. | |
| We also know that the test's false positive rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 847. The sensitivity of a test is 90% and its precision is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 848. The false omission rate of a test is 85%. | |
| We also know that the test's specificity is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 849. The false discovery rate of a test is 90%. | |
| We also know that the test's false positive rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 850. The false discovery rate of a test is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 851. The sensitivity of a test is 90% and its false omission rate is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 852. The sensitivity of a test is 90%. | |
| We also know that the test's false omission rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 853. The false negative rate of a test is 90%. | |
| We also know that the test's false omission rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 854. The false negative rate of a test is 95% and its specificity is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 855. The precision of a test is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 856. The sensitivity of a test is 95% and its negative predictive value is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the precision of the test? | |
| 857. The false omission rate of a test is 90% and its precision is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the false negative rate of the test? | |
| 858. The precision of a test is 90% and its sensitivity is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the specificity of the test? | |
| 859. The false discovery rate of a test is 85% and its negative predictive value is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 860. The specificity of a test is 95% and its negative predictive value is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the false omission rate of the test? | |
| 861. The negative predictive value of a test is 90% and its false negative rate is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 862. The false omission rate of a test is 85% and its specificity is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the precision of the test? | |
| 863. The false discovery rate of a test is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 864. The false omission rate of a test is 90% and its specificity is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 865. The false omission rate of a test is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 866. The negative predictive value of a test is 90%. | |
| We also know that the test's specificity is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 867. The sensitivity of a test is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 868. The false positive rate of a test is 95% and its false omission rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the sensitivity of the test? | |
| 869. The negative predictive value of a test is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 870. The false negative rate of a test is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 871. The false positive rate of a test is 85% and its false negative rate is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the false discovery rate of the test? | |
| 872. The false negative rate of a test is 85%. | |
| We also know that the test's false omission rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 873. The false negative rate of a test is 95% and its false omission rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 874. The specificity of a test is 95% and its false discovery rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 875. The negative predictive value of a test is 90% and its precision is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the sensitivity of the test? | |
| 876. The negative predictive value of a test is 90%. | |
| We also know that the test's specificity is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 877. The false positive rate of a test is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 878. The specificity of a test is 95% and its precision is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 879. The specificity of a test is 95%. | |
| We also know that the test's negative predictive value is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 880. The false positive rate of a test is 95% and its false discovery rate is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 881. The false positive rate of a test is 85% and its precision is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the sensitivity of the test? | |
| 882. The false omission rate of a test is 90%. | |
| We also know that the test's false positive rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 883. The negative predictive value of a test is 95% and its specificity is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the precision of the test? | |
| 884. The false discovery rate of a test is 90% and its sensitivity is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the false negative rate of the test? | |
| 885. The false positive rate of a test is 95% and its false omission rate is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 886. The precision of a test is 95%. | |
| We also know that the test's specificity is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 887. The false positive rate of a test is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 888. The sensitivity of a test is 85% and its false discovery rate is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the false omission rate of the test? | |
| 889. The false discovery rate of a test is 85% and its false omission rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the sensitivity of the test? | |
| 890. The false omission rate of a test is 90%. | |
| We also know that the test's false discovery rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 891. The precision of a test is 85% and its false positive rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 892. The false omission rate of a test is 85% and its false discovery rate is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 893. The false discovery rate of a test is 95% and its sensitivity is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the negative predictive value of the test? | |
| 894. The false omission rate of a test is 85%. | |
| We also know that the test's sensitivity is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 895. The precision of a test is 90% and its false negative rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the negative predictive value of the test? | |
| 896. The false omission rate of a test is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 897. The false negative rate of a test is 85% and its false omission rate is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the false positive rate of the test? | |
| 898. The false positive rate of a test is 90% and its false negative rate is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 899. The false positive rate of a test is 85% and its negative predictive value is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the precision of the test? | |
| 900. The precision of a test is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 901. The specificity of a test is 85% and its false discovery rate is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 902. The sensitivity of a test is 90% and its specificity is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the false discovery rate of the test? | |
| 903. The specificity of a test is 90% and its false discovery rate is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 904. The specificity of a test is 85% and its precision is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 905. The false discovery rate of a test is 85% and its false positive rate is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 906. The sensitivity of a test is 85%. | |
| We also know that the test's false discovery rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 907. The sensitivity of a test is 90% and its false omission rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the specificity of the test? | |
| 908. The negative predictive value of a test is 90%. | |
| We also know that the test's false negative rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 909. The false positive rate of a test is 85%. | |
| We also know that the test's precision is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 910. The false negative rate of a test is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 911. The negative predictive value of a test is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 912. The false omission rate of a test is 90%. | |
| We also know that the test's precision is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 913. The negative predictive value of a test is 95% and its false negative rate is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 914. The false discovery rate of a test is 95% and its sensitivity is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the specificity of the test? | |
| 915. The false negative rate of a test is 85% and its false discovery rate is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 916. The false positive rate of a test is 90% and its precision is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the sensitivity of the test? | |
| 917. The sensitivity of a test is 95% and its false positive rate is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the false discovery rate of the test? | |
| 918. The negative predictive value of a test is 95%. | |
| We also know that the test's precision is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 919. The negative predictive value of a test is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 920. The negative predictive value of a test is 85%. | |
| We also know that the test's precision is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 921. The negative predictive value of a test is 95% and its false negative rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 922. The false negative rate of a test is 85%. | |
| We also know that the test's false discovery rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 923. The false negative rate of a test is 90% and its specificity is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the precision of the test? | |
| 924. The false omission rate of a test is 95% and its specificity is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the false negative rate of the test? | |
| 925. The sensitivity of a test is 95% and its false discovery rate is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the specificity of the test? | |
| 926. The false omission rate of a test is 95%. | |
| We also know that the test's sensitivity is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 927. The specificity of a test is 95%. | |
| We also know that the test's negative predictive value is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 928. The false positive rate of a test is 90% and its sensitivity is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the precision of the test? | |
| 929. The specificity of a test is 95% and its false negative rate is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the false discovery rate of the test? | |
| 930. The precision of a test is 85%. | |
| We also know that the test's specificity is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 931. The precision of a test is 85%. | |
| We also know that the test's negative predictive value is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 932. The false omission rate of a test is 95%. | |
| We also know that the test's false negative rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 933. The false positive rate of a test is 95%. | |
| We also know that the test's negative predictive value is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 934. The false negative rate of a test is 90%. | |
| We also know that the test's specificity is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 935. The sensitivity of a test is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 936. The sensitivity of a test is 95% and its negative predictive value is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the precision of the test? | |
| 937. The false omission rate of a test is 95% and its sensitivity is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the false positive rate of the test? | |
| 938. The precision of a test is 95% and its specificity is 95%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 939. The false discovery rate of a test is 85%. | |
| We also know that the test's sensitivity is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 940. The false discovery rate of a test is 95% and its negative predictive value is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the false negative rate of the test? | |
| 941. The negative predictive value of a test is 85% and its false discovery rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the false negative rate of the test? | |
| 942. The false omission rate of a test is 95% and its sensitivity is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 943. The precision of a test is 95% and its specificity is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 944. The false negative rate of a test is 95%. | |
| We also know that the test's false positive rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 945. The precision of a test is 85% and its false positive rate is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the sensitivity of the test? | |
| 946. The sensitivity of a test is 95% and its false positive rate is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the negative predictive value of the test? | |
| 947. The precision of a test is 85%. | |
| We also know that the test's sensitivity is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 948. The false negative rate of a test is 95%. | |
| We also know that the test's false positive rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 949. The false discovery rate of a test is 95% and its negative predictive value is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 950. The false positive rate of a test is 95%. | |
| We also know that the test's false discovery rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 951. The false discovery rate of a test is 90% and its false positive rate is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the sensitivity of the test? | |
| 952. The precision of a test is 95%. | |
| We also know that the test's sensitivity is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 953. The specificity of a test is 85% and its sensitivity is 85%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 10%. | |
| What would be the precision of the test? | |
| 954. The sensitivity of a test is 85%. | |
| We also know that the test's false positive rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 955. The specificity of a test is 85%. | |
| We also know that the test's false omission rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 956. The false negative rate of a test is 90% and its false omission rate is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the false discovery rate of the test? | |
| 957. The specificity of a test is 85% and its sensitivity is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 958. The specificity of a test is 90% and its false negative rate is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the false discovery rate of the test? | |
| 959. The precision of a test is 95% and its false omission rate is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 960. The false discovery rate of a test is 85%. | |
| We also know that the test's sensitivity is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 961. The false omission rate of a test is 95%. | |
| We also know that the test's false discovery rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 962. The false negative rate of a test is 85%. | |
| We also know that the test's specificity is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 963. The sensitivity of a test is 85% and its negative predictive value is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the false discovery rate of the test? | |
| 964. The specificity of a test is 90% and its false discovery rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 965. The false positive rate of a test is 90%. | |
| We also know that the test's sensitivity is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 966. The false omission rate of a test is 90%. | |
| We also know that the test's false discovery rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 967. The precision of a test is 85% and its false omission rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 968. The false omission rate of a test is 85% and its false positive rate is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the specificity of the test? | |
| 969. The sensitivity of a test is 85%. | |
| We also know that the test's specificity is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 970. The negative predictive value of a test is 95%. | |
| We also know that the test's false positive rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 971. The specificity of a test is 85% and its negative predictive value is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the false discovery rate of the test? | |
| 972. The false omission rate of a test is 90%. | |
| We also know that the test's false negative rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 973. The sensitivity of a test is 95%. | |
| We also know that the test's specificity is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 974. The sensitivity of a test is 85%. | |
| We also know that the test's negative predictive value is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 975. The sensitivity of a test is 95% and its false discovery rate is 85%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 976. The false omission rate of a test is 90% and its false positive rate is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the false discovery rate of the test? | |
| 977. The false omission rate of a test is 90% and its precision is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 978. The precision of a test is 95%. | |
| We also know that the test's false negative rate is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 979. The precision of a test is 95% and its negative predictive value is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 980. The false discovery rate of a test is 85% and its false negative rate is 85%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a positive result? | |
| 981. The specificity of a test is 85%. | |
| We also know that the test's negative predictive value is 85% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 982. The false discovery rate of a test is 95% and its negative predictive value is 90%. | |
| We perform the test on a sick subject. | |
| What is the probability that the test will return a negative result? | |
| 983. The sensitivity of a test is 85% and its specificity is 85%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the negative predictive value of the test? | |
| 984. The specificity of a test is 95% and its negative predictive value is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 1%. | |
| What would be the precision of the test? | |
| 985. The specificity of a test is 85% and its false negative rate is 95%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 5%. | |
| What would be the negative predictive value of the test? | |
| 986. The negative predictive value of a test is 95%. | |
| We also know that the test's false positive rate is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 987. The negative predictive value of a test is 95%. | |
| We also know that the test's false negative rate is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 10%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 988. The precision of a test is 90% and its false omission rate is 90%. | |
| Assume we apply the test to a dataset where the proportion of positive test results is 1%. | |
| What would be the specificity of the test? | |
| 989. The false negative rate of a test is 95%. | |
| We also know that the test's negative predictive value is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a false positive? | |
| 990. The specificity of a test is 85% and its precision is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 991. The specificity of a test is 95% and its precision is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 992. The false omission rate of a test is 90%. | |
| We also know that the test's sensitivity is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a true negative? | |
| 993. The false positive rate of a test is 90%. | |
| We also know that the test's precision is 95% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 1%. | |
| We perform the test on a random subject, and it returns a positive result. | |
| What is the probability that it is a true positive? | |
| 994. The negative predictive value of a test is 90%. | |
| We also know that the test's precision is 90% and that these metrics were obtained | |
| when the test was evaluated on a dataset where the prevalence was 5%. | |
| We perform the test on a random subject, and it returns a negative result. | |
| What is the probability that it is a false negative? | |
| 995. The false negative rate of a test is 85% and its false positive rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 996. The negative predictive value of a test is 85% and its false positive rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 997. The false omission rate of a test is 85% and its false positive rate is 95%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a negative result? | |
| 998. The precision of a test is 85% and its false negative rate is 90%. | |
| We perform the test on a healthy subject. | |
| What is the probability that the test will return a positive result? | |
| 999. The false positive rate of a test is 95% and its negative predictive value is 95%. | |
| Assume we apply the test to a dataset where the prevalence is 10%. | |
| What would be the sensitivity of the test? | |
| 1000. The sensitivity of a test is 90% and its specificity is 90%. | |
| Assume we apply the test to a dataset where the prevalence is 5%. | |
| What would be the false omission rate of the test? |
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