**Chapter
45. **** ****Non -Parametric Tests** (.NET, C#, CSharp, VB, Visual Basic, F#)

Non-parametric (or distribution-free)
tests make no assumptions about the probability distributions of the
variables being assessed. **NMath Stats**
provides classes for several common non-parametric tests:

● Class **OneSampleKSTest**
performs a Kolmogorov-Smirnov test of the
distribution of one sample.

● Class **TwoSampleKSTest**
performs a two-sample Kolmogorov-Smirnov test to compare
the distributions of values in two data sets.

● Class **ShapiroWilkTest**
tests the null hypothesis that the sample comes from a normally distributed
population.

● Class **OneSampleAndersonDarlingTest**
performs a Anderson-Darling test of the distribution
of one sample.

● Class **KruskalWallisTest**
performs a Kruskal-Wallis rank sum test.

● Class **WilcoxonSignedRankTest**
performs a Wilcoxon signed-rank test for comparing
the means between two paired samples, or repeated measurements on a single
sample.

This chapter describes the non-parametric test classes.

See Section 38.9 for Spearman's rank correlation coefficient,
commonly known as *Spearman's rho*.