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A Non-Parametric Test of Independence
The Annals of Mathematical Statistics
Vol. 19, No. 4 (Dec., 1948), pp. 546-557
Published by: Institute of Mathematical Statistics
Stable URL: http://www.jstor.org/stable/2236021
Page Count: 12
You can always find the topics here!Topics: Nonparametric models, Rank tests, Random variables, Significance level, Mathematical functions, Statistics
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A test is proposed for the independence of two random variables with continuous distribution function (d.f.). The test is consistent with respect to the class Ω" of d.f.'s with continuous joint and marginal probability densities (p.d.). The test statistic D depends only on the rank order of the observations. The mean and variance of D are given and $\sqrt n(D - ED)$ is shown to have a normal limiting distribution for any parent distribution. In the case of independence this limiting distribution is degenerate, and nD has a non-normal limiting distribution whose characteristic function and cumulants are given. The exact distribution of D in the case of independence for samples of size n = 5, 6, 7 is tabulated. In the Appendix it is shown that there do not exist tests of independence based on ranks which are unbiased on any significance level with respect to the class Ω". It is also shown that if the parent distribution belongs to Ω" and for some n ≥ 5 the probabilities of the n! rank permutations are equal, the random variables are independent.
The Annals of Mathematical Statistics © 1948 Institute of Mathematical Statistics