Abstract
Statistical inference is based generally on some estimates that are functions of the data. Resampling methods offer strategies to estimate or approximate the sampling distribution of a statistic. In this article, two resampling methods are studied, jackknife and bootstrap, where the main objective is to examine the accuracy of these methods in estimating the distribution of the regression parameters through different sample sizes and different bootstrap replications.Keywords: Jackknife, Bootstrap, Multiple regression, Bias , Variance.
The article was added to IASJ on 2012-05-17
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