scipy.stats.mstats.ttest_ind¶

scipy.stats.mstats.ttest_ind(a, b, axis=0, equal_var=True)[source]¶

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

Parameters:

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. New in version 0.17.0.
Returns:	statistic : float or array The calculated t-statistic. pvalue : float or array The two-tailed p-value.

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.

New in version 0.17.0.

Returns:

Notes

For more details on ttest_ind, see stats.ttest_ind.