stats.weightstats.ttest_ind()

statsmodels.stats.weightstats.ttest_ind

statsmodels.stats.weightstats.ttest_ind(x1, x2, alternative='two-sided', usevar='pooled', weights=(None, None), value=0) [source]

ttest independent sample

convenience function that uses the classes and throws away the intermediate results, compared to scipy stats: drops axis option, adds alternative, usevar, and weights option

Parameters:

x1, x2 : array_like, 1-D or 2-D 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 weights : tuple of None or ndarrays Case weights for the two samples. For details on weights see DescrStatsW 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