`scipy.stats._mstats_basic:kurtosis`

source: /scipy/stats/_mstats_basic.py :2863

Signature

def kurtosis ( a , axis = 0 , fisher = True , bias = True )

Summary

Computes the kurtosis (Fisher or Pearson) of a dataset.

Extended Summary

Kurtosis is the fourth central moment divided by the square of the variance. If Fisher's definition is used, then 3.0 is subtracted from the result to give 0.0 for a normal distribution.

If bias is False then the kurtosis is calculated using k statistics to eliminate bias coming from biased moment estimators

Use kurtosistest to see if result is close enough to normal.

Parameters

a : array: data for which the kurtosis is calculated
axis : int or None, optional: Axis along which the kurtosis is calculated. Default is 0. If None, compute over the whole array a.
fisher : bool, optional: If True, Fisher's definition is used (normal ==> 0.0). If False, Pearson's definition is used (normal ==> 3.0).
bias : bool, optional: If False, then the calculations are corrected for statistical bias.

Returns

kurtosis : array: The kurtosis of values along an axis. If all values are equal, return -3 for Fisher's definition and 0 for Pearson's definition.

Notes

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

Aliases

scipy.stats._mstats_basic.kurtosis