The R Book (Google eBook)

Front Cover
John Wiley & Sons, Jun 13, 2007 - Mathematics - 950 pages
8 Reviews
The high-level language of R is recognized as one of the most powerful and flexible statistical software environments, and is rapidly becoming the standard setting for quantitative analysis, statistics and graphics. R provides free access to unrivalled coverage and cutting-edge applications, enabling the user to apply numerous statistical methods ranging from simple regression to time series or multivariate analysis.

Building on the success of the authorís bestselling Statistics: An Introduction using R, The R Book is packed with worked examples, providing an all inclusive guide to R, ideal for novice and more accomplished users alike. The book assumes no background in statistics or computing and introduces the advantages of the R environment, detailing its applications in a wide range of disciplines.

  • Provides the first comprehensive reference manual for the R language, including practical guidance and full coverage of the graphics facilities.
  • Introduces all the statistical models covered by R, beginning with simple classical tests such as chi-square and t-test.
  • Proceeds to examine more advance methods, from regression and analysis of variance, through to generalized linear models, generalized mixed models, time series, spatial statistics, multivariate statistics and much more.

The R Book is aimed at undergraduates, postgraduates and professionals in science, engineering and medicine. It is also ideal for students and professionals in statistics, economics, geography and the social sciences.

  

What people are saying - Write a review

User ratings

5 stars
4
4 stars
1
3 stars
0
2 stars
3
1 star
0

Review: The R Book

User Review  - Sam - Goodreads

It's hard to find a good R-Book. This one did the job for me while I was learning, but you will be lost if you are not on r-seek constantly filling the gaps. This book also requires a strong stomach ... Read full review

Review: The R Book

User Review  - Peter Flom - Goodreads

The best thing about this large book on R is its breadth: No one book can cover all of R, but this covers a lot. The biggest problem is the index and contents, which could have been better done and which could have made the book more usable Read full review

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
16 Proportion Data
569
17 Binary Response Variables
593
18 Generalized Additive Models
611
19 MixedEffects Models
627
20 Nonlinear Regression
661
21 Tree Models
685
22 Time Series Analysis
701
23 Multivariate Statistics
731

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
24 Spatial Statistics
749
25 Survival Analysis
787
26 Simulation Models
811
27 Changing the Look of Graphics
827
References and Further Reading
873
Index
877
Copyright

Common terms and phrases

References to this book

All Book Search results »

About the author (2007)

Michael Crawley is Professor at Imperial College at Silwood Park. He is a fellow of the Royal Society and author of the bestselling titles Statistics: An Introduction using R and Statistical Computing: An Introduction to Data Analysis Using S-Plus.

Bibliographic information