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 
 - 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.