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 Biologyillustrates 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. It provides comprehensive coverage of computer-intensive applications, with datasets available online. Features <ul> <li>Presents an overview of computer-intensive statistical methods and applications in biology</li> <li>Covers a wide range of methods including bootstrap, Monte Carlo, ANOVA, regression and Bayesian methods</li> <li>Makes it easy for biologists, researchers, and students to understand the methods used</li> <li>Provides information about computer programs and packages to implement calculations, particularly using R code</li> <li>Includes a large number of real examples from a range of biological disciplines</li> </ul> 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.

Randomization, Bootstrap and Monte Carlo Methods in Biology (Chapman & Hall/CRC Texts in Statistical Science)

Science & Math

Manly, Bryan F.J.

Navarro Alberto, Jorge A.

Mathematics

Routledge

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.

Chapman and Hall/CRC

Multivariate Statistical Methods

Gerow, Ken

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Books by Navarro Alberto, Jorge A.