statsmodels.stats.weightstats.CompareMeans.ttest_ind¶
method
- 
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
- alternativestring
 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
- usevarstring, ‘pooled’ or ‘unequal’
 If
pooled, then the standard deviation of the samples is assumed to be the same. Ifunequal, then Welsh ttest with Satterthwait degrees of freedom is used- valuefloat
 difference between the means under the Null hypothesis.
- Returns
 - tstatfloat
 test statisic
- pvaluefloat
 pvalue of the t-test
- dfint or float
 degrees of freedom used in the t-test
Notes
The result is independent of the user specified ddof.
