Chichester, West Sussex : Wiley, A John Wiley & Sons Ltd., Publicaton, 2013
1 online resource
QA276.45.R3 C73 2013
System Control No.
"Hugely successful and popular text presenting an extensive and comprehensive guide for all R users The R language is recognized as one of the most powerful and flexible statistical software packages, enabling users to apply many statistical techniques that would be impossible without such software to help implement such large data sets. R has become an essential tool for understanding and carrying out research.This edition: Features full colour text and extensive graphics throughout. Introduces a clear structure with numbered section headings to help readers locate information more efficiently. Looks at the evolution of R over the past five years. Features a new chapter on Bayesian Analysis and Meta-Analysis. Presents a fully revised and updated bibliography and reference section. Is supported by an accompanying website allowing examples from the text to be run by the user. Praise for the first edition:'...if you are an R user or wannabe R user, this text is the one that should be on your shelf. The breadth of topics covered is unsurpassed when it comes to texts on data analysis in R.' (The American Statistician, August 2008)'The High-level software language of R is setting standards in quantitative analysis. And now anybody can get to grips with it thanks to The R Book...' (Professional Pensions, July 2007) "-- Provided by publisher "This edition introduces the advantages of the R environment, in a user-friendly format, to beginners and intermediate users in a range of disciplines, from science and engineering to medicine and economics"-- Provided by publisher
Machine generated contents note: Preface vii 1 Getting Started 1 2 Essentials of the R Language 9 3 Data Input 97 4 Dataframes 107 5 Graphics 135 6 Tables 183 7 Mathematics 195 8 Classical Tests 279 9 Statistical Modelling 323 10 Regression 387 11 Analysis of Variance 449 12 Analysis of Covariance 489 13 Generalized Linear Models 511 14 Count Data 527 15 Count Data in Tables 549 16 Proportion Data 569 17 Binary Response Variables 593 18 Generalized Additive Models 611 19 Mixed-Effects Models 627 20 Non-linear Regression 661 21 Meta-analysis xxx 22 Bayesian statistics xxx 23 Tree Models 685 24 Time Series Analysis 701 25 Multivariate Statistics 731 26 Spatial Statistics 749 27 Survival Analysis 787 28 Simulation Models 811 29 Changing the Look of Graphics
Bibliography, etc. Note
Includes bibliographical references and index
Formatted Contents Note
Preface 1. Getting Started 2. Essentials of the R Language 3. Data Input 4. Dataframes 5. Graphics 6 Tables 7. Mathematics 8. Classical Tests 9. Statistical Modelling 10. Regression 11. Analysis of Variance 12. Analysis of Covariance 13. Generalized Linear Models 14. Count Data 15. Count Data in Tables 16. Proportion Data 17. Binary Response Variables 18. Generalized Additive Models 19. Mixed-Effects Models 20. Non-linear Regression 21. Meta-analysis 22. Bayesian statistics 23. Tree Models 24. Time Series Analysis 25. Multivariate Statistics 26. Spatial Statistics 27. Survival Analysis 28. Simulation Models 29. Changing the Look of Graphics
Source of Description
Description based on online resource; title from digital title page (viewed on December 31, 2012)
Available in Other Form
Print version: Crawley, Michael J. R book 2e.