套件： libstatistics-normality-perl (0.01-1)

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.