The Bootstrap and Edgeworth Expansion

The Bootstrap is a statistical method that estimates the variability of a result by repeatedly resampling data with replacement, helping assess the accuracy of estimates like averages or proportions. Edgeworth Expansion improves this by providing a more accurate approximation of a probability distribution beyond the normal approximation, incorporating skewness and other factors. Essentially, while the Bootstrap checks the reliability of results through resampling, Edgeworth Expansion refines probability estimates by adjusting for deviations from normality, both working together to give a clearer picture of data behavior and uncertainty.