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.
General
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