The bootstrap method is a statistical technique used to estimate the distribution of a sample statistic by resampling with replacement from the original data. This approach allows researchers to create multiple simulated samples, which helps in assessing the variability and confidence intervals of estimates, such as means or medians. This method is particularly useful when the underlying distribution of the data is unknown or when the sample size is small. By generating a large number of resampled datasets, the bootstrap method provides a robust way to make inferences about the population from which the original sample was drawn.