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Randomization Bootstrap And Monte Carlo Methods In Biology at Meripustak

Randomization Bootstrap And Monte Carlo Methods In Biology

Books from same Author: Bryan F.J. Manly Jorge A. Navarro Alberto

Books from same Publisher: Taylor & Francis Ltd

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    • General Information  
    Author(s)Bryan F.J. Manly Jorge A. Navarro Alberto
    PublisherTaylor & Francis Ltd
    EditionEdition New edition
    ISBN9780367349943
    Pages338
    BindingPaperback
    LanguageEnglish
    Publish YearJuly 2020

    Description

    Taylor & Francis Ltd Randomization Bootstrap And Monte Carlo Methods In Biology by Bryan F.J. Manly Jorge A. Navarro Alberto

    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.FeaturesPresents an overview of computer-intensive statistical methods and applications in biologyCovers a wide range of methods including bootstrap Monte Carlo ANOVA regression and Bayesian methodsMakes it easy for biologists researchers and students to understand the methods usedProvides information about computer programs and packages to implement calculations particularly using R codeIncludes a large number of real examples from a range of biological disciplinesWritten 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.show more