- statsmodels.stats.weightstats.ttest_ind(x1, x2, alternative='two-sided', usevar='pooled', weights=(None, None), value=0)¶
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.
- 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
The alternative hypothesis, H1, has to be one of the following
‘two-sided’ (default): H1: difference in means not equal to value
‘larger’ : H1: difference in means larger than value
‘smaller’ : H1: difference in means smaller than value
str, ‘pooled’ or ‘unequal’
pooled, then the standard deviation of the samples is assumed to be the same. If
unequal, then Welch ttest with Satterthwait degrees of freedom is used
Case weights for the two samples. For details on weights see
difference between the means under the Null hypothesis.