sábado, 21 de enero de 2012

The R Book

(Michael J Crawley)

Description: 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.

 Contents:
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 Mixed-Effects Models
20 Non-linear Regression
21 Tree Models
22 Time Series Analysis
23 Multivariate Statistics
24 Spatial Statistics
25 Survival Analysis
26 Simulation Models 
27 Changing the Look of Graphics
References and Further Reading 
Index 

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