Bootstrapping, a computational nonparametric technique for 're-sampling', enables researchers to draw a conclusion about the characteristics of a population strictly from the existing sample rather than by making parametric assumptions about the estimator. Using real data examples from per capita personal income to median preference differences between legislative committee members and the entire legislature, Mooney and Duval discuss how to apply bootstrapping when the underlying sampling distribution of the statistics cannot be assumed normal, as well as when the sampling distribution has no...

Monte Carlo simulation is a method of evaluating substantive hypotheses and statistical estimators by developing a computer algorithm to simulate a population, drawing multiple samples from this pseudo-population, and evaluating estimates obtained from these samples. This book explains the logic behind the method.