Computes the kurtosis (Fisher or Pearson) of a dataset.
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.
a : array
axis : int or None
fisher : bool
bias : bool
kurtosis : array
[CRCProbStat2000] Section 2.2.25
|[CRCProbStat2000]||(1, 2) Zwillinger, D. and Kokoska, S. (2000). CRC Standard Probability and Statistics Tables and Formulae. Chapman & Hall: New York. 2000.|