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If you're considering R for statistical computing and data visualization, this book provides a quick and practical guide to just about everything you can do with the open source R language and software environment. You'll learn how to write R functions and use R packages to help you prepare, visualize, and analyze data. Author Joseph Adler illustrates each process with a wealth of examples from medicine, business, and sports.
Updated for R 2.14 and 2.15, this second edition includes new and expanded chapters on R performance, the ggplot2 data visualization package, and parallel R computing with Hadoop. Get started quickly with an R tutorial and hundreds of examples Explore R syntax, objects, and other language details Find thousands of user-contributed R packages online, including Bioconductor Learn how to use R to prepare data for analysis Visualize your data with R's graphics, lattice, and ggplot2 packages Use R to calculate statistical fests, fit models, and compute probability distributions Speed up intensive computations by writing parallel R programs for Hadoop Get a complete desktop reference to R
List of contents
Preface
R Basics
Chapter 1: Getting and Installing R
Chapter 2: The R User Interface
Chapter 3: A Short R Tutorial
Chapter 4: R Packages
The R Language
Chapter 5: An Overview of the R Language
Chapter 6: R Syntax
Chapter 7: R Objects
Chapter 8: Symbols and Environments
Chapter 9: Functions
Chapter 10: Object-Oriented Programming
Working with Data
Chapter 11: Saving, Loading, and Editing Data
Chapter 12: Preparing Data
Data Visualization
Chapter 13: Graphics
Chapter 14: Lattice Graphics
Chapter 15: ggplot2
Statistics with R
Chapter 16: Analyzing Data
Chapter 17: Probability Distributions
Chapter 18: Statistical Tests
Chapter 19: Power Tests
Chapter 20: Regression Models
Chapter 21: Classification Models
Chapter 22: Machine Learning
Chapter 23: Time Series Analysis
Additional Topics
Chapter 24: Optimizing R Programs
Chapter 25: Bioconductor
Chapter 26: R and Hadoop
R Reference
Bibliography
Colophon
About the author
Joseph Adler has years of experience working with lots of popular data mining packages, including databases (including Oracle, PostgreSQL, and MS Access), statistical analysis tools (SAS, SPSS, S-Plus, and R), and data mining tools (SAS Enterprise Miner, Insightful Miner, Oracle Data Mining, Weka, and SPSS Clementine). He is currently leading a project at Verisign to pick a data mining package for enterprise deployment.
Summary
R is rapidly becoming the standard for developing statistical software, and R in a Nutshell provides a quick and practical way to learn this increasingly popular open source language and environment.
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"I am excited about this book. R in a Nutshell is a great introduction to R, as well as a comprehensive reference for using R in data analytics and visualization. Adler provides 'real world' examples, practical advice, and scripts, making it accessible to anyone working with data, not just professional statisticians." - Martin Schultz, Arthur K. Watson Professor of Computer Science, Yale University
