Author Question: Differentiate between the Kruskal-Wallis test and the one-way analysis of variance in terms of their ... (Read 117 times)

B · **on:** Jun 24, 2018

Differentiate between the Kruskal-Wallis test and the one-way analysis of variance in terms of their assumptions and the circumstances under which each should be applied.

Question 2

What is the parametric counterpart to the Wilcoxon rank sum test? Compare the assumptions involved in using the respective tests.

rleezy04 · **Reply #1 on:** Jun 24, 2018

Answer to Question 1

The one-way analysis of variance test assumes that samples have been drawn from normally distributed populations with equal variances. In addition, data must be of the interval or ratio scale. The Kruskal-Wallis test requires neither normal populations nor equal variances. The data must be at least ordinal, and the samples are assumed to be randomly selected. The one-way ANOVA test is preferred whenever the necessary assumptions are met.

Answer to Question 2

The parametric counterpart to the Wilcoxon rank sum test is the two-sample pooled-variances t-test for independent samples. The t-test assumes data on the interval or ratio scale, independent random samples, normally-distributed populations, and equal variances. The Wilcoxon rank sum test assumes data on the ordinal, interval, or ratio scale and that the samples are independent random samples from populations with similar shapes.