## An Introduction to the BootstrapStatistics is a subject of many uses and surprisingly few effective practitioners. The traditional road to statistical knowledge is blocked, for most, by a formidable wall of mathematics. The approach in An Introduction to the Bootstrap avoids that wall. It arms scientists and engineers, as well as statisticians, with the computational techniques they need to analyze and understand complicated data sets. |

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### Contents

The accuracy of a sample mean | 10 |

Random samples and probabilities | 17 |

The empirical distribution function and the plugin | 31 |

Standard errors and estimated standard errors | 39 |

The bootstrap estimate of standard error | 45 |

some examples | 60 |

More complicated data structures | 86 |

Regression models | 105 |

Crossvalidation and other estimates of prediction | 237 |

Adaptive estimation and calibration | 258 |

Assessing the error in bootstrap estimates | 271 |

A geometrical representation for the bootstrap | 283 |

An overview of nonparametric and parametric | 296 |

Further topics in bootstrap confidence intervals | 321 |

Efficient bootstrap computations | 338 |

Approximate likelihoods | 358 |

Estimates of bias | 124 |

The jackknife | 141 |

Confidence intervals based on bootstrap tables | 153 |

Confidence intervals based on bootstrap | 168 |

Better bootstrap confidence intervals | 178 |

Permutation tests | 202 |

Hypothesis testing with the bootstrap | 220 |

Bootstrap bioeguivalence | 372 |

Discussion and further topics | 392 |

software for bootstrap computations | 398 |

413 | |

Author index | 426 |

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### Common terms and phrases

ABC intervals algorithm approximation boot bootstrap computations bootstrap confidence intervals bootstrap data set bootstrap replications bootstrap samples calculations calibration Chapter components compute confidence intervals confidence point cross-validation curve data points defined delta method Denote density discussed distribution F distribution function Efron empirical distribution empirical distribution function endpoints equal estimate bias estimate of bias estimate of standard estimate of variance example exponential family Fisher information formula gives histogram hormone data hypothesis test infinitesimal jackknife jackknife estimate least-squares left panel linear matrix median mouse data nonparametric normal distribution normal theory null hypothesis number of bootstrap observed obtained panel of Figure parameter parametric bootstrap percentile interval permutation test plug-in estimate population prediction error probability distribution problem quadratic random sample random variable regression resampling right panel shows standard deviation standard error standard normal strap Suppose Table theta tion vector