17.5.6 Kruskal-Wallis ANOVA

1 Introduction
2 Handling Missing Values
3 Performing Kruskal-Wallis ANOVA

Introduction

The Kruskal-Wallis ANOVA is a nonparametric method for testing the equality of different samples' medians. The Kruskal-Wallis test is an extension of Mann-Whitney U test to three or more populations. This test requires that the populations are identically distributed. The null hypothesis is that all of the population medians are equal. The alternative hypothesis is that at least two of the population medians differ.

It is a powerful alternative to the one-way ANOVA. Unlike one-way ANOVA, Kruskal-Wallis ANOVA does not require normality of the populations. It places less restriction on the comparison, and therefore has wider applications.

Handling Missing Values

The missing values in the data range will be excluded in the analysis

From Origin 2015, missing values in the grouping range and the corresponding data values will be excluded in analysis. In the previous version, missing values in the grouping range will be considered as a group.

Performing Kruskal-Wallis ANOVA

To perform a Kruskal-Wallis ANOVA:

Select Statistics: Nonparametric Tests: Kruskal-Wallis ANOVA. This opens the kwanova dialog box.
Specify the Input Data.
Upon clicking OK, an analysis report sheet is generated showing the ranks table, degrees of freedom, Chi-square statistic, the associated p-value, and the test conclusion.