Introduction to Computer-Intensive Methods of Data Analysis in Biology

A 2006 graduate level introduction to modern computational tools for the analysis of biological data using S-PLUS.

Derek A. Roff (Author)

9780521608657, Cambridge University Press

Paperback, published 25 May 2006

378 pages, 48 b/w illus. 30 tables
24.4 x 17 x 2 cm, 0.6 kg

"The author's presentation of the material is meticulous in terms of organization and the use of well-defined notation. Nearly every method presented in the text has accompanying code in S-PLUS. Examples are interesting and most always involve real data. The topics are presented in a delightfully simple and intuitive fashion."
David H. Annis for The American Statistician

This 2006 guide to the contemporary toolbox of methods for data analysis will serve graduate students and researchers across the biological sciences. Modern computational tools, such as Maximum Likelihood, Monte Carlo and Bayesian methods, mean that data analysis no longer depends on elaborate assumptions designed to make analytical approaches tractable. These new 'computer-intensive' methods are currently not consistently available in statistical software packages and often require more detailed instructions. The purpose of this book therefore is to introduce some of the most common of these methods by providing a relatively simple description of the techniques. Examples of their application are provided throughout, using real data taken from a wide range of biological research. A series of software instructions for the statistical software package S-PLUS are provided along with problems and solutions for each chapter.

1. An introduction to computer intensive methods
2. Maximum likelihood
3. The Jack-knife
4. The Bootstrap
5. Randomisation
6. Regression methods
7. Bayesian methods
References
Exercises
Appendix A: an overview of S-Plus methods used in this book
Appendix B: brief description of S-Plus subroutines used in this book
Appendix C: S-Plus codes cited in text.

Subject Areas: Ecological science, the Biosphere [PSAF]