CompareMeans.ztest_ind()

statsmodels.stats.weightstats.CompareMeans.ztest_ind

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

z-test for the null hypothesis of identical means

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 the standard deviations of the samples may be different. value : float difference between the means under the Null hypothesis.

Returns:

tstat : float test statisic pvalue : float pvalue of the z-test