Chapter 19 Non-parametric Methods

A statistical method is called non-parametric if it makes no assumption on the population distribution or sample size.

This is in contrast with most parametric methods in elementary statistics that assume the data is quantitative, the population has a normal distribution and the sample size is sufficiently large.

In general, conclusions drawn from non-parametric methods are not as powerful as the parametric ones. However, as non-parametric methods make fewer assumptions, they are more flexible, more robust, and applicable to non-quantitative data.

19.1 Sign Test

19.2 Wilcoxon Signed-Rank Test

19.3 Mann-Whitney-Wilcoxon Test

19.4 Kruskal-Wallis Test