R in Action, 2nd Edition: Data Analysis and Graphics with R

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

PART 1 GETTING STARTED
Chapter 1. Introduction to R
Chapter 2. Creating a dataset
Chapter 3. Getting started with graphs
Chapter 4. Basic data management
Chapter 5. Advanced data management

PART 2 BASIC METHODS
Chapter 1. Basic graphs
Chapter 2. Basic statistics

PART 3 INTERMEDIATE METHODS
Chapter 1. Regression
Chapter 2. Analysis of variance
Chapter 3. Power analysis
Chapter 4. Intermediate graphs
Chapter 5. Resampling statistics and bootstrapping

PART 4 ADVANCED METHODS
Chapter 1. Generalized linear models
Chapter 2. Principal components and factor analysis
Chapter 3. Time series
Chapter 4. Cluster analysis
Chapter 5. Classification
Chapter 6. Advanced methods for missing data

PART 5 EXPANDING YOUR SKILLS
Chapter 1. Advanced graphics with ggplot2
Chapter 2. Advanced programming
Chapter 3. Creating a package
Chapter 4. Creating dynamic reports
Chapter 5. Advanced graphics with the lattice package available online only from manning.com/kabacoff2