An Algorithm for Computing the Exact Distribution of the Kruskal-Wallis Test

Won Choi, Jae Won Lee, Myung Hoe Huh, Seung Ho Kang

Research output: Contribution to journalArticle

7 Citations (Scopus)


The Kruskal-Wallis test is a popular nonparametric test for comparing k independent samples. In this article we propose a new algorithm to compute the exact null distribution of the Kruskal-Wallis test. Generating the exact null distribution of the Kruskal-Wallis test is needed to compare several approximation methods. The 5% cut-off points of the exact null distribution which StatXact cannot produce are obtained as by-products. We also investigate graphically a reason that the exact and approximate distributions differ, and hope that it will be a useful tutorial tool to teach about the Kruskal-Wallis test in undergraduate course.

Original languageEnglish
Pages (from-to)1029-1040
Number of pages12
JournalCommunications in Statistics Part B: Simulation and Computation
Issue number4
Publication statusPublished - 2003 Nov 1


All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modelling and Simulation

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