Resampling (statistics)
In statistics, resampling is any of a variety of methods for doing one of the following:
- 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)
- Exchanging labels on data points when performing significance tests (permutation tests, also called exact tests, randomization tests, or re-randomization tests)
- Validating models by using random subsets (bootstrapping, cross validation)
Common resampling techniques include bootstrapping, jackknifing and permutation tests.
Read more about Resampling (statistics): Bootstrap, Jackknife, Comparison of Bootstrap and Jackknife, Cross-validation, Permutation Tests, See Also