R in Action

Summary

R in Action, Second Edition presents both the R language and the examples that make it so useful for business developers. Focusing on practical solutions, the book offers a crash course in statistics and covers elegant methods for dealing with messy and incomplete data that are difficult to analyze using traditional methods. You'll also master R's extensive graphical capabilities for exploring and presenting data visually. And this expanded second edition includes new chapters on time series analysis, cluster analysis, and classification methodologies, including decision trees, random forests, and support vector machines.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

About the Technology

Business pros and researchers thrive on data, and R speaks the language of data analysis. R is a powerful programming language for statistical computing. Unlike general-purpose tools, R provides thousands of modules for solving just about any data-crunching or presentation challenge you're likely to face. R runs on all important platforms and is used by thousands of major corporations and institutions worldwide.

About the Book

R in Action, Second Edition teaches you how to use the R language by presenting examples relevant to scientific, technical, and business developers. Focusing on practical solutions, the book offers a crash course in statistics, including elegant methods for dealing with messy and incomplete data. You'll also master R's extensive graphical capabilities for exploring and presenting data visually. And this expanded second edition includes new chapters on forecasting, data mining, and dynamic report writing.

What's Inside

• Complete R language tutorial
• Using R to manage, analyze, and visualize data
• Techniques for debugging programs and creating packages
• OOP in R
• Over 160 graphs

About the Author

Dr. Rob Kabacoff is a seasoned researcher and teacher who specializes in data analysis. He also maintains the popular Quick-R website at statmethods.net.

Table of Contents

1. PART 1 GETTING STARTED
2. Introduction to R
3. Creating a dataset
4. Getting started with graphs
5. Basic data management
6. Advanced data management
7. PART 2 BASIC METHODS
8. Basic graphs
9. Basic statistics
10. PART 3 INTERMEDIATE METHODS
11. Regression
12. Analysis of variance
13. Power analysis
14. Intermediate graphs
15. Resampling statistics and bootstrapping
16. PART 4 ADVANCED METHODS
17. Generalized linear models
18. Principal components and factor analysis
19. Time series
20. Cluster analysis
21. Classification
22. Advanced methods for missing data
23. PART 5 EXPANDING YOUR SKILLS
24. Advanced graphics with ggplot2
25. Advanced programming
26. Creating a package
27. Creating dynamic reports
28. Advanced graphics with the lattice package available online only from manning.com/kabacoff2

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