module for testing normal distribution of data

 Various situations call for testing whether an empirical sample can be
 presumed to have been drawn from a normally (Gaussian) distributed
 population, especially because many downstream significance tests depend upon
 the assumption of normality. Statistics::Normality implements some of the
 more well-known normality tests from the mathematical statistics literature,
 though there are also others that are not included. The tests here are all
 so-called omnibus tests that find departures from normality on the basis of
 skewness and/or kurtosis.
 .
 Note that, although the Kolmogorov-Smirnov test can also be used in this
 capacity, it is a distance test and therefore not advisable. This, and other
 distance tests (e.g. Chi-square) are not implemented here.