PROPHET StatGuide: Friedman's test
Friedman's test is used to test
the null hypothesis that
several treatment effects
(locations)
are equal for data in a two-way layout.
The full version of StatGuide for Friedman's test will be available in a
future release. In the meantime, to properly analyze and interpret
results of Friedman's 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
Friedman's 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.
- 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.
Do a keyword search of PROPHET
StatGuide.
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Last modified: March 14, 1997
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Examine the glossary.