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:¶
- 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
- alternative
str
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
- usevar
str
, ‘pooled’ or ‘unequal’ If
pooled
, then the standard deviation of the samples is assumed to be the same. Ifunequal
, then Welch ttest with Satterthwait degrees of freedom is used- weights
tuple
of
None
orndarrays
Case weights for the two samples. For details on weights see
DescrStatsW
- value
float
difference between the means under the Null hypothesis.
- Returns:¶