scipy.stats.mstats.normaltest¶

scipy.stats.mstats.normaltest(a, axis=0)[source]¶

Tests whether a sample differs from a normal distribution.

Parameters:

Parameters:	a : array_like The array containing the data to be tested. axis : int or None, optional Axis along which to compute test. Default is 0. If None, compute over the whole array a.
Returns:	statistic : float or array `s^2 + k^2`, where `s` is the z-score returned by `skewtest` and `k` is the z-score returned by `kurtosistest`. pvalue : float or array A 2-sided chi squared probability for the hypothesis test.

a : array_like

The array containing the data to be tested.

axis : int or None, optional

Axis along which to compute test. Default is 0. If None, compute over the whole array a.

Returns:

statistic : float or array

s^2 + k^2, where s is the z-score returned by skewtest and k is the z-score returned by kurtosistest.

pvalue : float or array

A 2-sided chi squared probability for the hypothesis test.

Notes

For more details about normaltest, see stats.normaltest.