Joseph Adler

R in a Nutshell (eBook, ePUB)

A Desktop Quick Reference

• Format: ePub

Produktbeschreibung

If youre 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. Youll 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 examplesExplore R syntax, objects, and other language detailsFind thousands of user-contributed R packages online, including BioconductorLearn how to use R to prepare data for analysisVisualize your data with Rs graphics, lattice, and ggplot2 packagesUse R to calculate statistical fests, fit models, and compute probability distributionsSpeed up intensive computations by writing parallel R programs for HadoopGet a complete desktop reference to R

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Produktdetails

• Verlag: O'Reilly Media
• Seitenzahl: 724
• Erscheinungstermin: 26. September 2012
• Englisch
• ISBN-13: 9781449358228
• Artikelnr.: 38312143

Autorenporträt

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.

Inhaltsangabe

1. Preface
2. R Basics
* Chapter 1: Getting and Installing R
* Chapter 2: The R User Interface
* Chapter 3: A Short R Tutorial
* Chapter 4: R Packages
3. 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
4. Working with Data
* Chapter 11: Saving, Loading, and Editing Data
* Chapter 12: Preparing Data
5. Data Visualization
* Chapter 13: Graphics
* Chapter 14: Lattice Graphics
* Chapter 15: ggplot2
6. 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
7. Additional Topics
* Chapter 24: Optimizing R Programs
* Chapter 25: Bioconductor
* Chapter 26: R and Hadoop
8. R Reference
9. Bibliography
10. Colophon