Resampling is any technique of generating a new sample from an existing dataset.
There is a variety of methods for 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).
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If you want to look for more information, check some free online courses available at coursera.org, edx.org or udemy.com.
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