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This title in other editions

The R Book

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The R Book Cover

 

Synopses & Reviews

Publisher Comments:

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)

Synopsis:

The R language is recognized as one of the most powerful and flexible statistical software packages, and it enables the user to apply many statistical techniques that would be impossible without such software to help implement such large data sets. R is becoming essential both to carry out research and to understand it, as more and more people present their results in the context of R.

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. The format enables it to be either read as a text, or dipped-into as a reference manual.

The early chapters assume no background in statistics or computing, and introduce the reader to the basic concepts involved. In this way the reader is introduced to the assumptions that lie behind the tests, fostering a critical approach to statistical modeling. These early chapters have been thoroughly updated to take account of the way language has evolved since the publication of the first edition. Subsequent chapters examine more advanced topics, cementing what is learnt in the opening chapters, as well as benefiting more intermediate readers. Throughout the book, the reader's experience is furthered by practical guidance and the inclusion of numerous worked examples.

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

Product Details

ISBN:
9780470973929
Author:
Crawley, Michael J.
Publisher:
John Wiley & Sons
Author:
Michael J.
Author:
Crawley
Subject:
Statistics
Subject:
Computational & Graphical Statistics
Subject:
R environment, R how to, R text, R guide, statistical software, statistical software user guide, data analysis techniques, statistical modeling
Subject:
Mathematics | Probability and Statistics
Subject:
Statistical Software / R
Subject:
R environment, R how to, R text, R guide, statistical software, statistical software user guide, data analysis techniques, statistical modeli
Subject:
Ng
Subject:
R environment, R how to, R text, R guide, statistical software, statistical software user guide, data
Subject:
analysis techniques, statistical modeling
Copyright:
Edition Description:
WOL online Book (not BRO)
Publication Date:
20130110
Binding:
HARDCOVER
Language:
English
Pages:
1076
Dimensions:
246 x 189 mm

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Related Subjects

Computers and Internet » Computers Reference » General
Computers and Internet » Software Engineering » Programming and Languages
Health and Self-Help » Health and Medicine » Medical Specialties
Science and Mathematics » Mathematics » General
Science and Mathematics » Mathematics » Probability and Statistics » General
Science and Mathematics » Mathematics » Probability and Statistics » Statistics
Science and Mathematics » Mathematics » Software

The R Book New Hardcover
0 stars - 0 reviews
$103.75 In Stock
Product details 1076 pages John Wiley & Sons - English 9780470973929 Reviews:
"Synopsis" by , The R language is recognized as one of the most powerful and flexible statistical software packages, and it enables the user to apply many statistical techniques that would be impossible without such software to help implement such large data sets. R is becoming essential both to carry out research and to understand it, as more and more people present their results in the context of R.

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. The format enables it to be either read as a text, or dipped-into as a reference manual.

The early chapters assume no background in statistics or computing, and introduce the reader to the basic concepts involved. In this way the reader is introduced to the assumptions that lie behind the tests, fostering a critical approach to statistical modeling. These early chapters have been thoroughly updated to take account of the way language has evolved since the publication of the first edition. Subsequent chapters examine more advanced topics, cementing what is learnt in the opening chapters, as well as benefiting more intermediate readers. Throughout the book, the reader's experience is furthered by practical guidance and the inclusion of numerous worked examples.

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