Overview

Introduction -- The accuracy of a sample mean -- Random samples and probabilities -- The empirical distribution function and the plug-in principle -- Standard errors and estimated standard errors -- The bootstrap estimate of standard error-- Bootstrap standard errors: some examples -- More complicated data structures -- Regression models -- The jackknife -- Confidence intervals based on bootstrap "tables" -- Confidence intervals based on bootstrap percentiles -- Better bootstrap confidence intervals -- Permutation tests -- Hypothesis testing with the bootstrap -- Cross-validation and other estimates of prediction error -- Adaptive estimation and calibration -- Assessing the error in bootstrap estimates -- A geometrical representation for the bootstrap and jackknife -- An overview of nonparametric and parametric inference -- Further topics in bootstrap confidence intervals -- Efficient bootstrap computations -- Approximate likelihoods -- Bootstrap bioequivalence