One Sample T-Test Using Only Summary Statistics

Single Sample T-Test Using Summary Stats

import scipy.stats as stats
import math

def one_sample_ttest_pval(tail, mu, x, s, n, alpha):

    #Calculate test statistic and p-value. Provide summary stats and specify 1 or 2 tailed test
    t = round((x - mu) / (s / math.sqrt(n)),2)
    test_stat = round(stats.t.ppf(q=alpha, 
            df=n-1),3)
    if tail == 1:
        pval = round(stats.t.cdf(t,      
                   df= n-1),4)
        print("Results for a 1-tailed t-test:")
    elif tail == 2:
        pval = round((1 - stats.t.cdf(t,      
                   df= n-1))* 2, 4)
        print("Results for a 2-tailed t-test:")
        
    #Print test results
    print("Test statistic = {}".format(test_stat))   
    print("P-value = {}".format(pval))
    print("Confidence = {}".format(alpha))
    
    #Compare p-value to confidence level
    if pval <= alpha:
        print("{} <=  {}. Reject the null hypothesis.".format(pval, alpha))
    else:
        print("{} > {}. Do not reject the null hypothesis.".format(pval, alpha))
        
    
    
#Sample tests:


#one_sample_ttest_pval(2, 600, 612, 65, 40, .05)


#one_sample_ttest_pval(1, 238, 231, 80, 100, .05)