Modern computer-intensive statistical methods play a key role in solving many problems across a wide range of scientific disciplines. This new edition of the bestselling Randomization, Bootstrap and Monte Carlo Methods in Biology illustrates the value of a number of these methods with an emphasis on biological applications.

This textbook focuses on three related areas in computational statistics: randomization, bootstrapping, and Monte Carlo methods of inference. The author emphasizes the sampling approach within randomization testing and confidence intervals. Similar to randomization, the book shows how bootstrapping, or resampling, can be used for confidence intervals and tests of significance. It also explores how to use Monte Carlo methods to test hypotheses and construct confidence intervals.

New to the Third Edition

  • Updated information on regression and time series analysis, multivariate methods, survival and growth data as well as software for computational statistics
  • References that reflect recent developments in methodology and computing techniques
  • Additional references on new applications of computer-intensive methods in biology

    Providing comprehensive coverage of computer-intensive applications while also offering data sets online, Randomization, Bootstrap and Monte Carlo Methods in Biology, Third Edition supplies a solid foundation for the ever-expanding field of statistics and quantitative analysis in biology.
  • chapter 1|28 pages


    chapter 2|12 pages

    The Jackknife

    chapter 3|40 pages

    The Bootstrap

    chapter 4|12 pages

    Monte Carlo Methods

    chapter 5|14 pages

    Some General Considerations

    chapter 6|28 pages

    One- and Two-Sample Tests

    chapter 7|34 pages

    Analysis of Variance

    chapter 8|34 pages

    Regression Analysis

    chapter 9|36 pages

    Distance Matrices and Spatial Data

    chapter 10|22 pages

    Other Analyses on Spatial Data

    chapter 11|40 pages

    Time Series

    chapter 12|24 pages

    Multivariate Data

    chapter 13|16 pages

    Survival and Growth Data

    chapter 14|30 pages

    Nonstandard Situations

    chapter 15|10 pages

    Bayesian Methods

    chapter 16|4 pages

    Final Comments