resample

Resampling is a statistical process that involves repeatedly drawing samples from a dataset to estimate the variability or uncertainty of a statistic or model. Imagine taking multiple "snapshots" of your data to see how a measured value might change if the experiment or survey were repeated. Techniques like bootstrapping and cross-validation are common resampling methods, helping to evaluate the stability of results, improve model accuracy, or select the best model by leveraging different portions of the data. Resampling ensures that conclusions are more reliable and not overly dependent on a single dataset snapshot.