Bootstrap Method

The bootstrap method is a statistical technique used to estimate the accuracy of a result, such as the average of a data set. It works by repeatedly taking random samples from the original data, with replacement (meaning some data points can be chosen more than once), and recalculating the result each time. This process creates many "simulated" datasets, allowing us to assess how much the results might vary if we collected new data. Ultimately, the bootstrap helps us understand the reliability and variability of our estimates without needing additional data collection.