The R Book

by
Edition: 2nd
Format: eBook
Pub. Date: 2012-11-07
Publisher(s): Wiley
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Summary

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) 

Table of Contents

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 827

References and Further Reading 873

Index 877s

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