The Bootstrap (Statistical Method)

Bootstrapping is a statistical method used to estimate the properties of a sample by resampling it. Imagine you have a small set of data, like test scores from students. Bootstrapping involves repeatedly taking random samples from this data, with replacement, to create many simulated datasets. By analyzing these datasets, you can estimate things like averages or confidence intervals, giving you insights about the larger population. This technique is particularly useful when the actual population data is unavailable or difficult to collect, providing a way to make informed statistical inferences from limited information.