Bootstrapping

Bootstrapping is a statistical method that involves repeatedly taking samples from a dataset, with replacement, to estimate the variability or uncertainty of a result. Imagine having a dataset and wanting to understand how reliable a statistic (like a mean or median) is—bootstrapping creates many new "sample datasets" by randomly selecting data points, some of which may be repeated. Analyzing these multiple samples helps assess the stability of the statistic without needing additional data. It’s a powerful technique for making inference when data is limited, leveraging the existing data to approximate the range of possible outcomes.