Introduction to Computer-Intensive Methods of Data Analysis in Biology
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.
- Each chapter has exercises and solutions which allow the reader to check their understanding
- Real biological data examples are used throughout to demonstrate the applications of the techniques
- Provides S-Plus coding so that the reader can carry out the statistical tests described
Reviews & endorsements
"The strength of the work is its coverage of contemporary, computer-intensive methods and the detailed templates provided for implementing each one. Many people learn most quickly by working through an example that resembles a problem of their own, and so I think this aspect of the book will be widely appreciated."
N. Thompson Hobbs for Ecology
"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
Product details
June 2006Paperback
9780521608657
378 pages
244 × 170 × 20 mm
0.6kg
48 b/w illus. 30 tables
Available
Table of Contents
- 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.