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Statistical hypothesis tests based on Matrix data.
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package se.alipsa.groovy.stats.normality
/**
* D'Agostino's K2 test, named for Ralph D'Agostino, is a goodness-of-fit measure of departure from normality,
* that is the test aims to gauge the compatibility of given data with the null hypothesis that the data is a
* realization of independent, identically distributed Gaussian random variables.
* The test is based on transformations of the sample kurtosis and skewness, and has power only against the
* alternatives that the distribution is skewed and/or kurtic.
*/
class KSquared {
}