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R in a Nutshell (In a Nutshell)

by

R in a Nutshell (In a Nutshell) Cover

 

Synopses & Reviews

Publisher Comments:

Why learn R? Because it's rapidly becoming the standard for developing statistical software. R in a Nutshell provides a quick and practical way to learn this increasingly popular open source language and environment. You'll not only learn how to program in R, but also how to find the right user-contributed R packages for statistical modeling, visualization, and bioinformatics.

The author introduces you to the R environment, including the R graphical user interface and console, and takes you through the fundamentals of the object-oriented R language. Then, through a variety of practical examples from medicine, business, and sports, you'll learn how you can use this remarkable tool to solve your own data analysis problems.

  • Understand the basics of the language, including the nature of R objects
  • Learn how to write R functions and build your own packages
  • Work with data through visualization, statistical analysis, and other methods
  • Explore the wealth of packages contributed by the R community
  • Become familiar with the lattice graphics package for high-level data visualization
  • Learn about bioinformatics packages provided by Bioconductor

"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

Synopsis:

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 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 Rs 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

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.

Table of Contents

PrefaceR BasicsChapter 1: Getting and Installing RChapter 2: The R User InterfaceChapter 3: A Short R TutorialChapter 4: R PackagesThe R LanguageChapter 5: An Overview of the R LanguageChapter 6: R SyntaxChapter 7: R ObjectsChapter 8: Symbols and EnvironmentsChapter 9: FunctionsChapter 10: Object-Oriented ProgrammingWorking with DataChapter 11: Saving, Loading, and Editing DataChapter 12: Preparing DataData VisualizationChapter 13: GraphicsChapter 14: Lattice GraphicsChapter 15: ggplot2Statistics with RChapter 16: Analyzing DataChapter 17: Probability DistributionsChapter 18: Statistical TestsChapter 19: Power TestsChapter 20: Regression ModelsChapter 21: Classification ModelsChapter 22: Machine LearningChapter 23: Time Series AnalysisAdditional TopicsChapter 24: Optimizing R ProgramsChapter 25: BioconductorChapter 26: R and HadoopR ReferenceBibliographyColophon

Product Details

ISBN:
9781449312084
Author:
Adler, Joseph
Publisher:
O'Reilly Media
Subject:
Mathematics -- Software.
Subject:
analysis;analysis of variance;data;data analysis;data modelling;data visualization;graphics;informatics;r;statistics;variance;visualization
Copyright:
Edition Description:
Trade paper
Publication Date:
20121016
Binding:
Paperback
Language:
English
Pages:
724
Dimensions:
9 x 6 in

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Related Subjects

Computers and Internet » Computer Languages » The Attic
Computers and Internet » Computers Reference » General
Science and Mathematics » Mathematics » Software

R in a Nutshell (In a Nutshell) New Trade Paper
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Product details 724 pages O'Reilly Media - English 9781449312084 Reviews:
"Synopsis" by ,

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 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 Rs 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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