NMath User's Guide

TOC | Previous | Next | Index

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.