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. .. versionadded:: 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. .. versionadded:: 0.17.0

Returns:

statistic : float or array

The calculated t-statistic.

pvalue : float or array

The two-tailed p-value.

Notes

For more details on ttest_ind, see stats.ttest_ind.

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