Introduction to Computer-Intensive Methods of Data Analysis in Biology (Hardback)
  • Introduction to Computer-Intensive Methods of Data Analysis in Biology (Hardback)
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Introduction to Computer-Intensive Methods of Data Analysis in Biology (Hardback)

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£113.00
Hardback 378 Pages / Published: 25/05/2006
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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.

Publisher: Cambridge University Press
ISBN: 9780521846288
Number of pages: 378
Weight: 800 g
Dimensions: 247 x 174 x 23 mm


MEDIA REVIEWS
"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

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