PROPHET StatGuide: Kruskal-Wallis test
The Kruskal-Wallis test is used to test the null hypothesis that
multiple population
distribution
functions (corresponding to multiple
samples)
are identical against the
alternative hypothesis
that they differ by
location.
The full version of StatGuide for the Kruskal-Wallis test will be available in a
future release. In the meantime, to properly analyze and interpret
results of the Kruskal-Wallis test, you should be familiar with the
following terms and concepts:
If you are not familiar with these terms and concepts, you are advised to
consult with a statistician. Failure to understand and properly apply the
Kruskal-Wallis test may result in drawing erroneous conclusions from your data.
Additionally, you may want to consult the following references:
- Brownlee, K. A. 1965. Statistical Theory and Methodology
in Science and Engineering. New York: John Wiley & Sons.
- Conover, W. J. 1980. Practical Nonparametric Statistics. 2nd ed.
New York: John Wiley & Sons.
- Daniel, Wayne W. 1978. Applied Nonparametric Statistics.
Boston: Houghton Mifflin.
- Daniel, Wayne W. 1995. Biostatistics. 6th ed.
New York: John Wiley & Sons.
- Hollander, M. and Wolfe, D. A. 1973. Nonparametric Statistical Methods.
New York: John Wiley & Sons.
- Lehmann, E. L. 1975. Nonparametrics: Statistical Methods Based on
Ranks. San Francisco: Holden-Day.
- Miller, Rupert G. Jr. 1986. Beyond ANOVA, Basics of Applied
Statistics. New York: John Wiley & Sons.
- Rosner, Bernard. 1995. Fundamentals of Biostatistics.
4th ed. Belmont, California: Duxbury Press.
- Sokal, Robert R. and Rohlf, F. James. 1995. Biometry. 3rd. ed.
New York: W. H. Freeman and Co.
- Zar, Jerrold H. 1996. Biostatistical Analysis. 3rd ed. Upper Saddle River, NJ:
Prentice-Hall.
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Last modified: March 18, 1997
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Examine the glossary.