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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
Inhaltsverzeichnis
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
Über den Autor / die Autorin
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.
Zusammenfassung
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.
Bericht
"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
