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Rank Transformations as a Bridge Between Parametric and Nonparametric Statistics
W. J. Conover and Ronald L. Iman
The American Statistician
Vol. 35, No. 3 (Aug., 1981), pp. 124-129
Stable URL: http://www.jstor.org/stable/2683975
Page Count: 6
You can always find the topics here!Topics: Statistics, Approximation, Applied statistics, Rank tests, Nonparametric methods, T distribution, Covariance, Nonparametric tests, Experiment design, Gaussian distributions
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Many of the more useful and powerful nonparametric procedures may be presented in a unified manner by treating them as rank transformation procedures. Rank transformation procedures are ones in which the usual parametric procedure is applied to the ranks of the data instead of to the data themselves. This technique should be viewed as a useful tool for developing nonparametric procedures to solve new problems.
The American Statistician © 1981 American Statistical Association