Bootstrap methods

Bootstrap methods are statistical techniques used to estimate the characteristics of a population by repeatedly sampling from a smaller dataset. Imagine you're baking a cake, but instead of using all the ingredients at once, you take a small spoonful to test the flavor. By mixing that spoonful back into the batter multiple times and tasting each time, you get a good idea of the overall flavor without using the entire cake. Similarly, bootstrap methods create many "resampled" datasets to assess estimates like averages or probabilities, allowing researchers to understand uncertainty and make reliable conclusions from limited data.