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Efron's bootstrap is a recently developed approach to nonparametric statistics, resampling from a set of observations to establish a basis for inference which is neither burdened with tenuous assumptions nor nonresponsive to distributional information carried by the data. In this article, the bootstrap approach is illustrated by developing nonparametric confidence intervals for the Pearson product-moment correlation. The technique is shown to be well within the capabilities of widely available eight-bit microcomputers.

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