AbstractResampling methods are statistical procedures that reuse the sample data for the purpose of statistical inference. However, they do not require parametric assumptions that may be difficult to verify in practice. This focus article describes four resampling techniques, the bootstrap, the jackknife, cross‐validation, and permutation tests. Another method, subsampling, is mentioned with two references but is not covered in any detail. These resampling methods and the history of their development are outlined in this paper. © 2012 Wiley Periodicals, Inc.This article is categorized under:Algorithmic Development > StatisticsTechnologies > Prediction