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New in the Third Edition:  Fully updated references  Additional examples and exercises from the social and environmental sciences  A comparison of the various statistical software packages, including Stata, Statistica, SAS Minitab, and Genstat, particularly in terms of their ease of use by beginners  In his efforts to produce a book that is as short as possible and that enables you to begin to use multivariate methods in an intelligent manner, the author has produced a succinct and handy reference. With updated information on multivariate analyses, new examples using the latest software, and updated references, this book provides a timely introduction to useful tools for statistical analysis.","brand":"WoB","offers":[{"title":"GB \/ VERY_GOOD \/ INTERNAL","offer_id":49625802113297,"sku":"GOR007934699","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"US \/ GOOD \/ SBYB","offer_id":50393066602769,"sku":"CIN1584884142G","price":0.0,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/1584884142.jpg?v=1751057132"},{"product_id":"randomization-and-monte-carlo-method-book-bryan-fj-manly-9780412367106","title":"Randomization and Monte Carlo Method","description":"This book aims to illustrate the value of modern computer intensive methods for a wide range of statistical problems. There is coverage of randomization methods of inference that were first proposed by R.A. Fisher in 1935, but are only now becoming practical because of the ready availability of computer power. Applications to analysis of variance and regression multivariate analysis are covered. Monte Carlo methods, jacknifing and bootstrapping are also discussed as being alternatives to randomization in some circumstances. The examples used have been chosen to attract interest and include the controversial topics of whether there is periodicity in fossil extinction records and whether there is evidence for a relationship between species co-occurences on islands. The first chapter introduces the ideas of randomization methods through some examples and the second introduces Monte Carlo tests and also the computer intensive techniques of jacknifing and bootstrapping since these are sometimes used as alternatives to randomization. The following chapters discuss some general theoretical matters concerning randomization and Monte Carlo methods and the analysis of various standard types of data. The final chapter gives some examples of non-standard situations where computer intensive methods seem to provide the best method for statistical analysis. 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This second edition illustrates the value of modern computer intensive methods in the solution of a wide range of problems, with particular emphasis on biological applications. Examples given in the text include the controversial topic of whether there is periodicity between co-occurrences of species on islands.","brand":"WoB","offers":[{"title":"US \/ GOOD \/ SBYB","offer_id":50106947993873,"sku":"CIN0412721309G","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ VERY_GOOD \/ INTERNAL","offer_id":52083000967441,"sku":"GOR006651576","price":0.0,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/0412721309.jpg?v=1751390933"},{"product_id":"statistics-for-environmental-science-and-management-book-bryan-fj-manly-9781420061475","title":"Statistics for Environmental Science and Management","description":"Suitable for graduate courses and a reference for appropriate statistical approaches to specific environmental problems, this title begins by describing the important role statistics play in environmental science. 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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. 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