An Introduction to the Bootstrap

Series:
Chapman & Hall/CRC Monographs on Statistics & Applied Probability
Published:
May 15, 1994 by Chapman and Hall/CRC - 456 Pages
Author(s):
Bradley Efron, Stanford University, Palo Alto, California, USA; R.J. Tibshirani, Stanford University, California, USA

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Hardback
$119.95
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ISBN 9780412042317
Cat# C4231
 

Features

  • Exposes readers to many exciting and useful statistical techniques through real data examples, such as the mouse data, the stamp data, the tooth data and the hormone data
  • Describes various techniques, including nonparametric regression, density estimation, classification trees, and least median squares regression
  • Includes numerous exercises--some involving computing--that provide hands-on experience in applying the concepts and techniques
  • Contains descriptions of a number of different computer programs for the methods discussed
  • Offers a presentation accessible to non-specialists--scientists, engineers, and doctors--that will help them streamline their quantitative research

    • Summary

    Statistics 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.

    Table of Contents

    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
    Estimates of Bias
    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
    Discussion and Further Topics
    Appendix: Software for Bootstrap Computations
    References

    Editorial Reviews

    "...an excellent book, and worth a reading by most students and practitioners in statistics... Throughout the book, the authors have spent a lot of effort in introducing difficult ideas in a simple, easy-to-understand manner..."
    - Hong Kong Statistical Society Newsletter

    "... written in a style that makes difficult statistical concepts easy to understand ...a wonderful text for the engineer who would like to apply and understand the many different bootstrap techniques that have appeared in the literature in the last fifteen years. It makes an excellent reference text that should grace the shelves of both statisticians and non-statisticians."
    - Journal of Quality Technology

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