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:

x1array_like, 1-D or 2-D: first of the two independent samples, see notes for 2-D case
x2array_like, 1-D or 2-D: second of the two independent samples, see notes for 2-D case
alternativestr: 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
usevarstr, ‘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.
valuefloat: difference between the means under the Null hypothesis.

Returns: