Edition 
Second edition 
Descript 
1 online resource 

text txt rdacontent 

computer c rdamedia 

online resource cr rdacarrier 
Note 
"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 MetaAnalysis. 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 Highlevel 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 userfriendly format, to beginners and intermediate users in a range of disciplines, from science and engineering to medicine and economics" Provided by publisher 

Includes bibliographical references and index 

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 MixedEffects Models 627 20 Nonlinear Regression 661 21 Metaanalysis 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 

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. MixedEffects Models  20. Nonlinear Regression  21. Metaanalysis  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 

Description based on online resource; title from digital title page (viewed December 31, 2012) 
Link 
Print version: Crawley, Michael J. R book
2e. 9780470973929
(DLC) 2012027339

Subject 
R (Computer program language)


Mathematical statistics  Data processing


MATHEMATICS  Probability & Statistics  General.
bisacsh


Electronic books

