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Abstract

With the ever-increasing use of computers in data analysis, there has been a movement to abandon traditional parametric approaches, with all of their restrictive assumptions, in favor of computer-intensive nonparametric inferential statistical procedures such as the jackknife and the bootstrap that are based upon resampling of the sample data. In this article these techniques are compared and contrasted with the parametric approach, with special emphasis on inferences regarding correlation coefficients.

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