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orome/SE question 22716521 - Python output

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SE question 22716521 - Python output
Generalized Linear Model Regression Results
=================================================================================================
Dep. Variable: ['over50k[ <=50K]', 'over50k[ >50K]'] No. Observations: 19187
Model: GLM Df Residuals: 19090
Model Family: Binomial Df Model: 96
Link Function: logit Scale: 1.0
Method: IRLS Log-Likelihood: nan
Date: Fri, 28 Mar 2014 Deviance: nan
Time: 11:32:05 Pearson chi2: 4.75e+05
No. Iterations: 11
================================================================================================================
coef std err t P>|t| [95.0% Conf. Int.]
----------------------------------------------------------------------------------------------------------------
Intercept 10.6766 5.985 1.784 0.074 -1.055 22.408
workclass[T. Federal-gov] -0.9775 4.498 -0.217 0.828 -9.794 7.839
workclass[T. Local-gov] -0.2395 4.498 -0.053 0.958 -9.055 8.576
workclass[T. Never-worked] 8.8346 114.394 0.077 0.938 -215.374 233.043
workclass[T. Private] -0.4732 4.497 -0.105 0.916 -9.288 8.341
workclass[T. Self-emp-inc] -0.6296 4.498 -0.140 0.889 -9.446 8.187
workclass[T. Self-emp-not-inc] -0.0576 4.498 -0.013 0.990 -8.873 8.758
workclass[T. State-gov] -0.2733 4.498 -0.061 0.952 -9.090 8.544
workclass[T. Without-pay] 10.0745 85.048 0.118 0.906 -156.616 176.765
education[T. 11th] 0.1139 1.012 0.113 0.910 -1.870 2.098
education[T. 12th] 0.0348 1.977 0.018 0.986 -3.841 3.911
education[T. 1st-4th] -0.6382 3.971 -0.161 0.872 -8.421 7.145
education[T. 5th-6th] -0.6923 2.964 -0.234 0.815 -6.503 5.118
education[T. 7th-8th] -0.3230 1.976 -0.163 0.870 -4.196 3.550
education[T. 9th] -0.2106 1.039 -0.203 0.839 -2.248 1.826
education[T. Assoc-acdm] 0.4168 5.846 0.071 0.943 -11.041 11.874
education[T. Assoc-voc] 0.1414 4.873 0.029 0.977 -9.409 9.692
education[T. Bachelors] 0.1779 6.819 0.026 0.979 -13.186 13.542
education[T. Doctorate] 0.6034 9.741 0.062 0.951 -18.488 19.695
education[T. HS-grad] 0.0033 2.927 0.001 0.999 -5.733 5.740
education[T. Masters] 0.2704 7.792 0.035 0.972 -15.002 15.543
education[T. Preschool] 16.6916 88.028 0.190 0.850 -155.840 189.223
education[T. Prof-school] 0.0899 8.767 0.010 0.992 -17.093 17.273
education[T. Some-college] -0.0194 3.899 -0.005 0.996 -7.661 7.623
maritalstatus[T. Married-AF-spouse] -2.5398 0.714 -3.555 0.000 -3.940 -1.139
maritalstatus[T. Married-civ-spouse] -2.4578 0.357 -6.880 0.000 -3.158 -1.758
maritalstatus[T. Married-spouse-absent] 0.0949 0.320 0.296 0.767 -0.533 0.723
maritalstatus[T. Never-married] 0.4515 0.114 3.962 0.000 0.228 0.675
maritalstatus[T. Separated] -0.0361 0.198 -0.182 0.856 -0.425 0.353
maritalstatus[T. Widowed] -0.1858 0.196 -0.947 0.343 -0.570 0.199
occupation[T. Adm-clerical] -0.2227 4.497 -0.050 0.961 -9.037 8.592
occupation[T. Armed-Forces] 0.8796 4.713 0.187 0.852 -8.357 10.117
occupation[T. Craft-repair] -0.3453 4.497 -0.077 0.939 -9.159 8.469
occupation[T. Exec-managerial] -1.0680 4.497 -0.237 0.812 -9.882 7.746
occupation[T. Farming-fishing] 0.9403 4.499 0.209 0.834 -7.878 9.759
occupation[T. Handlers-cleaners] 0.4957 4.500 0.110 0.912 -8.323 9.315
occupation[T. Machine-op-inspct] 0.0582 4.498 0.013 0.990 -8.757 8.873
occupation[T. Other-service] 0.6904 4.498 0.153 0.878 -8.126 9.507
occupation[T. Priv-house-serv] 8.8400 29.530 0.299 0.765 -49.037 66.717
occupation[T. Prof-specialty] -0.7611 4.497 -0.169 0.866 -9.575 8.053
occupation[T. Protective-serv] -0.7547 4.499 -0.168 0.867 -9.572 8.062
occupation[T. Sales] -0.4556 4.497 -0.101 0.919 -9.270 8.359
occupation[T. Tech-support] -0.7452 4.498 -0.166 0.868 -9.561 8.071
occupation[T. Transport-moving] -0.1279 4.498 -0.028 0.977 -8.943 8.687
relationship[T. Not-in-family] -0.7881 0.353 -2.233 0.026 -1.480 -0.096
relationship[T. Other-relative] 0.2194 0.314 0.699 0.484 -0.395 0.834
relationship[T. Own-child] 0.7489 0.351 2.136 0.033 0.062 1.436
relationship[T. Unmarried] -0.7041 0.372 -1.893 0.058 -1.433 0.025
relationship[T. Wife] -1.3235 0.133 -9.942 0.000 -1.584 -1.063
race[T. Asian-Pac-Islander] -0.4830 0.355 -1.361 0.174 -1.178 0.213
race[T. Black] -0.3644 0.288 -1.265 0.206 -0.929 0.200
race[T. Other] -0.2204 0.451 -0.488 0.625 -1.105 0.664
race[T. White] -0.4108 0.274 -1.501 0.133 -0.947 0.126
sex[T. Male] -0.7729 0.102 -7.545 0.000 -0.974 -0.572
nativecountry[T. Canada] -0.2593 1.308 -0.198 0.843 -2.823 2.305
nativecountry[T. China] 0.9695 1.327 0.730 0.465 -1.632 3.571
nativecountry[T. Columbia] 1.9536 1.526 1.280 0.200 -1.037 4.945
nativecountry[T. Cuba] -0.0573 1.323 -0.043 0.965 -2.651 2.536
nativecountry[T. Dominican-Republic] 10.4271 42.755 0.244 0.807 -73.370 94.224
nativecountry[T. Ecuador] 0.0355 1.477 0.024 0.981 -2.860 2.931
nativecountry[T. El-Salvador] 0.6095 1.395 0.437 0.662 -2.125 3.343
nativecountry[T. England] 0.0671 1.327 0.051 0.960 -2.533 2.668
nativecountry[T. France] -0.5301 1.419 -0.374 0.709 -3.310 2.250
nativecountry[T. Germany] -0.0547 1.306 -0.042 0.967 -2.615 2.506
nativecountry[T. Greece] 2.6463 1.714 1.544 0.123 -0.712 6.005
nativecountry[T. Guatemala] 8.9257 45.295 0.197 0.844 -79.850 97.702
nativecountry[T. Haiti] 0.9221 1.615 0.571 0.568 -2.244 4.088
nativecountry[T. Holand-Netherlands] 8.8234 324.746 0.027 0.978 -627.668 645.315
nativecountry[T. Honduras] 0.9584 3.412 0.281 0.779 -5.728 7.645
nativecountry[T. Hong] 0.2362 1.492 0.158 0.874 -2.687 3.160
nativecountry[T. Hungary] -0.1412 1.555 -0.091 0.928 -3.190 2.907
nativecountry[T. India] 0.8218 1.314 0.625 0.532 -1.753 3.397
nativecountry[T. Iran] 0.0330 1.366 0.024 0.981 -2.644 2.710
nativecountry[T. Ireland] -0.1579 1.473 -0.107 0.915 -3.045 2.729
nativecountry[T. Italy] -0.6100 1.333 -0.458 0.647 -3.222 2.002
nativecountry[T. Jamaica] 0.2279 1.387 0.164 0.869 -2.490 2.946
nativecountry[T. Japan] -0.5072 1.375 -0.369 0.712 -3.202 2.188
nativecountry[T. Laos] 0.6831 1.661 0.411 0.681 -2.572 3.938
nativecountry[T. Mexico] 0.9182 1.303 0.705 0.481 -1.636 3.472
nativecountry[T. Nicaragua] 0.1987 1.507 0.132 0.895 -2.756 3.153
nativecountry[T. Outlying-US(Guam-USVI-etc)] 9.7305 115.066 0.085 0.933 -215.795 235.256
nativecountry[T. Peru] 0.9660 1.678 0.576 0.565 -2.323 4.255
nativecountry[T. Philippines] -0.0439 1.281 -0.034 0.973 -2.555 2.467
nativecountry[T. Poland] -0.2410 1.383 -0.174 0.862 -2.951 2.469
nativecountry[T. Portugal] -0.7276 1.477 -0.493 0.622 -3.623 2.168
nativecountry[T. Puerto-Rico] 0.5769 1.357 0.425 0.671 -2.083 3.237
nativecountry[T. Scotland] 1.1876 1.719 0.691 0.490 -2.181 4.556
nativecountry[T. South] 0.8183 1.341 0.610 0.542 -1.811 3.447
nativecountry[T. Taiwan] 0.2590 1.350 0.192 0.848 -2.387 2.905
nativecountry[T. Thailand] 1.6932 1.737 0.975 0.330 -1.711 5.098
nativecountry[T. Trinadad&Tobago] 1.3462 1.721 0.782 0.434 -2.027 4.719
nativecountry[T. United-States] 0.0859 1.269 0.068 0.946 -2.402 2.574
nativecountry[T. Vietnam] 1.0085 1.523 0.662 0.508 -1.976 3.993
nativecountry[T. Yugoslavia] -1.4018 1.648 -0.851 0.395 -4.631 1.827
age -0.0255 0.002 -11.916 0.000 -0.030 -0.021
educationnum -0.3364 0.974 -0.345 0.730 -2.246 1.573
capitalgain -0.0003 1.37e-05 -23.904 0.000 -0.000 -0.000
capitalloss -0.0006 4.85e-05 -13.277 0.000 -0.001 -0.001
hoursperweek -0.0290 0.002 -13.791 0.000 -0.033 -0.025
================================================================================================================
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