The R Book
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 author's 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
Review: The R BookUser 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 BookUser 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
16 Proportion Data
17 Binary Response Variables
18 Generalized Additive Models
19 MixedEffects Models
20 Nonlinear Regression
21 Tree Models
22 Time Series Analysis
23 Multivariate Statistics
8 Classical Tests
9 Statistical Modelling
11 Analysis of Variance
12 Analysis of Covariance
13 Generalized Linear Models
14 Count Data
15 Count Data in Tables