Overview

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 ...

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R in a Nutshell

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Overview

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
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Product Details

  • ISBN-13: 9781449358228
  • Publisher: O'Reilly Media, Incorporated
  • Publication date: 9/26/2012
  • Sold by: Barnes & Noble
  • Format: eBook
  • Edition number: 2
  • Pages: 724
  • Sales rank: 654,255
  • File size: 11 MB
  • Note: This product may take a few minutes to download.

Meet the Author

Joseph Adler has many years of experience in data mining and data analysis at companies including DoubleClick, American Express, and VeriSign. He graduated from MIT with an Sc.B and M.Eng in Computer Science and Electrical Engineering from MIT. He is the inventor of several patents for computer security and cryptography, and the author of Baseball Hacks. Currently, he is a senior data scientist at LinkedIn.

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Table 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

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