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Concept
Resampling (statistics)
Summary
In statistics, resampling is the creation of new samples based on one observed sample.
Resampling methods are:
Permutation tests (also re-randomization tests)
Bootstrapping
Cross validation
Permutation tests Permutation test Permutation tests rely on resampling the original data assuming the null hypothesis. Based on the resampled data it can be concluded how likely the original data is to occur under the null hypothesis. Bootstrap Bootstrap (statistics) Bootstrapping is a statistical method for estimating the sampling distribution of an estimator by sampling with replacement from the original sample, most often with the purpose of deriving robust estimates of standard errors and confidence intervals of a population parameter like a mean, median, proportion, odds ratio, correlation coefficient or regression coefficient. It has been called the plug-in principle, as it is the method of estimation of functionals of a population distribution by evaluating theOfficial source
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