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:

alternative{“two-sided”, “larger”, “smaller”}, optional: 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{“pooled”, “unequal”}, optional: 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.
valuefloat, optional: difference between the means under the Null hypothesis.

Returns: