scipy.stats.mstats.kurtosistest#
- scipy.stats.mstats.kurtosistest(a, axis=0, alternative='two-sided')[source]#
Tests whether a dataset has normal kurtosis
- 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
New 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
, seescipy.stats.kurtosistest
.