`scipy.stats._mstats_basic:ttest_ind`

source: /scipy/stats/_mstats_basic.py :1501

Signature

   def     ttest_ind (    a    ,    b    ,    axis    =  0   ,    equal_var    =  True   ,    alternative    =  two-sided     )

Summary

Calculates the T-test for the means of TWO INDEPENDENT samples of scores.

Parameters

a, b : array_like

The arrays must have the same shape, except in the dimension corresponding to axis (the first, by default).

axis : int or None, optional

Axis along which to compute test. If None, compute over the whole arrays, a, and b.

equal_var : bool, optional

If True, perform a standard independent 2 sample test that assumes equal population variances. If False, perform Welch's t-test, which does not assume equal population variance.

alternative : {'two-sided', 'less', 'greater'}, optional

Defines the alternative hypothesis. The following options are available (default is 'two-sided'):

'two-sided': the means of the distributions underlying the samples are unequal.
'less': the mean of the distribution underlying the first sample is less than the mean of the distribution underlying the second sample.
'greater': the mean of the distribution underlying the first sample is greater than the mean of the distribution underlying the second sample.

Returns

statistic : float or array: The calculated t-statistic.
pvalue : float or array: The p-value.

Notes

For more details on ttest_ind, see scipy.stats.ttest_ind.

Aliases

scipy.stats._mstats_basic.ttest_ind