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A New Test of Association for Continuous Variables

R. C. Elston and John Stewart
Biometrics
Vol. 26, No. 2 (Jun., 1970), pp. 305-314
DOI: 10.2307/2529077
Stable URL: http://www.jstor.org/stable/2529077
Page Count: 10
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Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
A New Test of Association for Continuous Variables
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Abstract

A new test statistic is proposed for detecting association between two continuous variables. For sample sizes of 20 or more, the statistic's distribution (when the variables are independent) is tolerably well approximated by a normal distribution. Expressions are given for determining the mean and variance of this distribution, so that a test can be performed. This test is very powerful against various types of alternatives for which a test based on the sample correlation coefficient is powerless. When the underlying distribution is bivariate normal, the sample correlation is appreciably better only if either the sample size is less than 50 or the true correlation is less than 0.5.

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