statsmodels.stats.weightstats.CompareMeans.ttest_ind

CompareMeans.ttest_ind(alternative='two-sided', usevar='pooled', value=0) [source]

ttest for the null hypothesis of identical means

this should also be the same as onewaygls, except for ddof differences

Parameters:

x2 (x1,) – two independent samples, see notes for 2-D case alternative (string) – The alternative hypothesis, H1, has to be one of the following ‘two-sided’: H1: difference in means not equal to value (default) ‘larger’ : H1: difference in means larger than value ‘smaller’ : H1: difference in means smaller than value usevar (string, 'pooled' or 'unequal') – If pooled, then the standard deviation of the samples is assumed to be the same. If unequal, then Welsh ttest with Satterthwait degrees of freedom is used value (float) – difference between the means under the Null hypothesis.

Returns:

tstat (float) – test statisic pvalue (float) – pvalue of the t-test df (int or float) – degrees of freedom used in the t-test

Notes

The result is independent of the user specified ddof.