Non-parametric (or distribution-free) inferential statistical methods are mathematical procedures for statistical hypothesis testing which, unlike parametric statistics, make no assumptions about the frequency distributions of the variables being assessed. The most widely used of these methods is probably the chi-square test. Other widely used non-parametric methods include Mann-Whitney U, the Kruskal-Wallis one-way analysis of variance, the median test, Spearman's &rho, and estimation of probability using the binomial distribution.

They may have more statistical power than a parametric test when the assumptions underlying the parametric test are not satisfied.

See also parametric statistics.