Resampling (statistics)

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Bol Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. In statistics, resampling is any of a variety of methods for doing one of the following: 1. Estimating the precision of sample statistics (medians, variances, percentiles) by using subsets of available data (jackknifing) or drawing randomly with replacement from a set of data points (bootstrapping). 2. Exchanging labels on data points when performing significance tests (permutation tests, also called exact tests, randomization tests, or re-randomization tests). 3. Validating models by using random subsets (bootstrapping, cross validation). Common resampling techniques include bootstrapping, jackknifing and permutation tests.
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Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. In statistics, resampling is any of a variety of methods for doing one of the following: 1. Estimating the precision of sample statistics (medians, variances, percentiles) by using subsets of available data (jackknifing) or drawing randomly with replacement from a set of data points (bootstrapping). 2. Exchanging labels on data points when performing significance tests (permutation tests, also called exact tests, randomization tests, or re-randomization tests). 3. Validating models by using random subsets (bootstrapping, cross validation). Common resampling techniques include bootstrapping, jackknifing and permutation tests.

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