scipy.stats.mstats.

kurtosistest#

scipy.stats.mstats.kurtosistest(a, axis=0, alternative='two-sided')[source]#

Tests whether a dataset has normal kurtosis

Deprecated since version 2.0.0: scipy.stats.mstats.kurtosistest is deprecated as of SciPy 2.0.0 and will be removed, along with the scipy.stats.mstats namespace, in SciPy 2.4.0. For similar functionality, use scipy.stats.kurtosistest with MArray(s) instead of NumPy masked array(s).

Parameters:
aarray_like

array of the sample data

axisint or None, optional

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

alternative{‘two-sided’, ‘less’, ‘greater’}, optional

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

  • ‘two-sided’: the kurtosis of the distribution underlying the sample is different from that of the normal distribution

  • ‘less’: the kurtosis of the distribution underlying the sample is less than that of the normal distribution

  • ‘greater’: the kurtosis of the distribution underlying the sample is greater than that of the normal distribution

Added in version 1.7.0.

Returns:
statisticarray_like

The computed z-score for this test.

pvaluearray_like

The p-value for the hypothesis test

Notes

For more details about kurtosistest, see scipy.stats.kurtosistest.

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