如果你選擇R語言用於統計計算和數據可視化，那麼《R語言技術手冊(影印版第2版)》將可以為你提供開源R語言及其軟件環境的快速實用指南。你將學習如何編寫R函數和使用R包來幫助你準備、可視化和分析數據。本書作者Joseph Adler(艾德勒)講解了來自醫藥、商業和體育方面大量實例的處理過程。
本次第二版*新基於R語言2.14和2.15版本，包括了這樣一些新的擴展章節：R性能、ggplot2數據可視化包和基於Hadoop的並行R計算。

Preface
Part Ⅰ. R Basics
1. Getting and Installing R
R Versions
Getting and Installing Interactive R Binaries
Windows
Mac OS X
Linux and Unix Systems
2. The R Userlnterface
The R Graphical User Interface
Windows
Mac OS X
Linux and Unix
The R Console
Command-Line Editing
Batch Mode
Using R Inside Microsoft Excel
RStudio
Other Ways to Run R
3. AShort RTutorial
Basic Operations in R
Functions
Variables
Introduction to Data Structures
Objects and Classes
Models and Formulas
Charts and Graphics
Getting Help
4. R Packages
An Overview of Packages
Listing Packages in Local Libraries
Loading Packages
Loading Packages on Windows and Linux
Loading Packages on Mac OS X
Exploring Package Repositories
Exploring R Package Repositories on the Web
Finding and Installing Packages Inside R
Installing Packages From Other Repositories
Custom Packages
Creating a Package Directory
Building the Package
Part Ⅱ. The R Language
5. An Overview of the R Language
Expressions
Objects
Symbols
Functions
Objects Are Copied in Assignment Statements
Everything in R Is an Object
Special Values
NA
Inf and -Inf
NaN
NULL
Coercion
The R Interpreter
Seeing How R Works
6. R Syntax
Constants
Numeric Vectors
Character Vectors
Symbols
Operators
Order of Operations
……
7. R Objects
8. Symbols and Environments
9. Functions.
10. Object-Oriented Programming
Part Ⅲ. Working with Data
11. Saving, Loading, and Editing Data
12. Preparing Data
Part Ⅳ. Data Visualization
13. Graphics
14. Lattice Graphics
15. ggplot2
Part Ⅴ. Statistics with R
16. Analyzing Data
17. Probability Distributions
18. Statistical Tests
19. Power Tests
20. Regression Models
21. Classification Models
22. Machine Learning
23. Time Series Analysis
Part Ⅵ. Additional Topics
24. Optimizing R Programs
25. Bioconductor
26. Rand Hadoop
Appendix: R Reference
Bibliography
Index