statsmodels.stats.weightstats.CompareMeans.ttest_ind¶
-
CompareMeans.ttest_ind(alternative=
'two-sided'
, usevar='pooled'
, value=0
)[source]¶ ttest for the null hypothesis of identical means
this should also be the same as onewaygls, except for ddof differences
- 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’: 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
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- value
float
difference between the means under the Null hypothesis.
- Returns:¶
Notes
The result is independent of the user specified ddof.
Last update:
Dec 11, 2024