Epidemiologists often deal with complex data and situations where assumptions of traditional statistical methods, such as normality, are violated. Resampling methods, like bootstrap and permutation tests, do not rely on these assumptions, making them versatile tools. They are particularly useful for estimating the precision of sample statistics (e.g., mean, median, proportion) and for hypothesis testing.
