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 comming 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
The kurtosis of values along an axis. If all values are equal, return -3 for Fisher’s :
definition and 0 for Pearson’s definition. :
[CRCProbStat2000] section 2.2.25