Randomization, Bootstrap and Monte Carlo Methods in Biology by Bryan Fj Manly

Randomization, Bootstrap and Monte Carlo Methods in Biology by Bryan Fj Manly

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Randomization, Bootstrap and Monte Carlo Methods in Biology

Randomization, Bootstrap and Monte Carlo Methods in Biology by Bryan Fj Manly

Modern computer-intensive statistical methods play a key role in solving many problems across a wide range of scientific disciplines. Like its bestselling predecessors, the fourth edition of Randomization, Bootstrap and Monte Carlo Methods in Biology illustrates a large number of statistical methods with an emphasis on biological applications. The focus is now on the use of randomization, bootstrapping, and Monte Carlo methods in constructing confidence intervals and doing tests of significance. The text provides comprehensive coverage of computer-intensive applications, with data sets available online. Features Presents an overview of computer-intensive statistical methods and applications in biology Covers a wide range of methods including bootstrap, Monte Carlo, ANOVA, regression, and Bayesian methods Makes it easy for biologists, researchers, and students to understand the methods used Provides information about computer programs and packages to implement calculations, particularly using R code Includes a large number of real examples from a range of biological disciplines Written in an accessible style, with minimal coverage of theoretical details, this book provides an excellent introduction to computer-intensive statistical methods for biological researchers. It can be used as a course text for graduate students, as well as a reference for researchers from a range of disciplines. The detailed, worked examples of real applications will enable practitioners to apply the methods to their own biological data.
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ISBN 13
Title Randomization, Bootstrap and Monte Carlo Methods in Biology
Author Bryan Fj Manly
Condition Unavailable
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Cover note Book picture is for illustrative purposes only, actual binding, cover or edition may vary.

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