Resampling

Part of speech: noun

Definitions

1. The methodology involves selecting and analyzing subsets from a comprehensive dataset to derive insights about the whole population while frequently drawing and comparing samples It incorporates both collecting new data points and evaluating variations within previously collected samples
2. Creating new data samples by repeatedly selecting observations to estimate statistical properties ; applying techniques that generate different subsets or arrangements of existing data to evaluate variability or improve model accuracy
3. Producing additional samples from a dataset to assess or improve the reliability of findings ; using data manipulation methods that repeatedly draw samples for analysis without collecting new data

Etymology: Resampling is a plain compound: "re-" meaning again, attached to "sampling," which comes from the Old French "essample," an example or a sample of something larger. A sample, in its older sense, was a single piece taken to show what the whole was like, and to sample something was to take such a piece for testing or inspection. Putting the two together, resampling means sampling again: drawing a fresh set of observations from data already in hand. The term belongs to the vocabulary of statistics and computing, where it describes methods such as bootstrapping and cross-validation, in which the same dataset is repeatedly subdivided or redrawn so that analysts can gauge how stable an estimate is. It is a technical coinage built from familiar parts, so its history is essentially the history of those two elements.