R in a Nutshell: A Desktop Quick Reference [NOOK Book]

Overview

What people are saying about R in a Nutshell
"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 ...
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R in a Nutshell: A Desktop Quick Reference

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Overview

What people are saying about R in a Nutshell
"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
"R in a Nutshell is an ideal book for getting started with R. Newcomers will find the fundamentals for performing statistical analysis and graphics, all illustrated with practical examples. This book is an invaluable reference for anyone who wants to learn what R is and what is can do, even for longtime R users looking for new tips and tricks."
--David M. Smith, Editor of the "Revolutions" blog at REvolution ComputingWhy 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
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Product Details

  • ISBN-13: 9781449383046
  • Publisher: O'Reilly Media, Incorporated
  • Publication date: 1/4/2010
  • Sold by: Barnes & Noble
  • Format: eBook
  • Edition number: 1
  • Pages: 636
  • Sales rank: 1,369,298
  • File size: 10 MB

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. He is the inventor of several patents for computer security and cryptography, and the author of Baseball Hacks and R in a Nutshell.

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Table of Contents

Preface; Why I Wrote This Book; When Should You Use R?; R License Terms; Examples; How This Book Is Organized; Conventions Used in This Book; Using Code Examples; How to Contact Us; SafariĀ® Books Online; Acknowledgments; R Basics; Chapter 1: Getting and Installing R; 1.1 R Versions; 1.2 Getting and Installing Interactive R Binaries; Chapter 2: The R User Interface; 2.1 The R Graphical User Interface; 2.2 The R Console; 2.3 Batch Mode; 2.4 Using R Inside Microsoft Excel; 2.5 Other Ways to Run R; Chapter 3: A Short R Tutorial; 3.1 Basic Operations in R; 3.2 Functions; 3.3 Variables; 3.4 Introduction to Data Structures; 3.5 Objects and Classes; 3.6 Models and Formulas; 3.7 Charts and Graphics; 3.8 Getting Help; Chapter 4: R Packages; 4.1 An Overview of Packages; 4.2 Listing Packages in Local Libraries; 4.3 Loading Packages; 4.4 Exploring Package Repositories; 4.5 Custom Packages; The R Language; Chapter 5: An Overview of the R Language; 5.1 Expressions; 5.2 Objects; 5.3 Symbols; 5.4 Functions; 5.5 Objects Are Copied in Assignment Statements; 5.6 Everything in R Is an Object; 5.7 Special Values; 5.8 Coercion; 5.9 The R Interpreter; 5.10 Seeing How R Works; Chapter 6: R Syntax; 6.1 Constants; 6.2 Operators; 6.3 Expressions; 6.4 Control Structures; 6.5 Accessing Data Structures; 6.6 R Code Style Standards; Chapter 7: R Objects; 7.1 Primitive Object Types; 7.2 Vectors; 7.3 Lists; 7.4 Other Objects; 7.5 Attributes; Chapter 8: Symbols and Environments; 8.1 Symbols; 8.2 Working with Environments; 8.3 The Global Environment; 8.4 Environments and Functions; 8.5 Exceptions; Chapter 9: Functions; 9.1 The Function Keyword; 9.2 Arguments; 9.3 Return Values; 9.4 Functions As Arguments; 9.5 Argument Order and Named Arguments; 9.6 Side Effects; Chapter 10: Object-Oriented Programming; 10.1 Overview of Object-Oriented Programming in R; 10.2 Object-Oriented Programming in R: S4 Classes; 10.3 Old-School OOP in R: S3; Chapter 11: High-Performance R; 11.1 Use Built-in Math Functions; 11.2 Use Environments for Lookup Tables; 11.3 Use a Database to Query Large Data Sets; 11.4 Preallocate Memory; 11.5 Monitor How Much Memory You Are Using; 11.6 Functions for Big Data Sets; 11.7 Parallel Computation with R; 11.8 High-Performance R Binaries; Working with Data; Chapter 12: Saving, Loading, and Editing Data; 12.1 Entering Data Within R; 12.2 Saving and Loading R Objects; 12.3 Importing Data from External Files; 12.4 Exporting Data; 12.5 Importing Data from Databases; Chapter 13: Preparing Data; 13.1 Combining Data Sets; 13.2 Transformations; 13.3 Binning Data; 13.4 Subsets; 13.5 Summarizing Functions; 13.6 Data Cleaning; 13.7 Finding and Removing Duplicates; 13.8 Sorting; Chapter 14: Graphics; 14.1 An Overview of R Graphics; 14.2 Graphics Devices; 14.3 Customizing Charts; Chapter 15: Lattice Graphics; 15.1 History; 15.2 An Overview of the Lattice Package; 15.3 High-Level Lattice Plotting Functions; 15.4 Customizing Lattice Graphics; 15.5 Low-Level Functions; Statistics with R; Chapter 16: Analyzing Data; 16.1 Summary Statistics; 16.2 Correlation and Covariance; 16.3 Principal Components Analysis; 16.4 Factor Analysis; 16.5 Bootstrap Resampling; Chapter 17: Probability Distributions; 17.1 Normal Distribution; 17.2 Common Distribution-Type Arguments; 17.3 Distribution Function Families; Chapter 18: Statistical Tests; 18.1 Continuous Data; 18.2 Discrete Data; Chapter 19: Power Tests; 19.1 Experimental Design Example; 19.2 t-Test Design; 19.3 Proportion Test Design; 19.4 ANOVA Test Design; Chapter 20: Regression Models; 20.1 Example: A Simple Linear Model; 20.2 Details About the lm Function; 20.3 Subset Selection and Shrinkage Methods; 20.4 Nonlinear Models; 20.5 Survival Models; 20.6 Smoothing; 20.7 Machine Learning Algorithms for Regression; Chapter 21: Classification Models; 21.1 Linear Classification Models; 21.2 Machine Learning Algorithms for Classification; Chapter 22: Machine Learning; 22.1 Market Basket Analysis; 22.2 Clustering; Chapter 23: Time Series Analysis; 23.1 Autocorrelation Functions; 23.2 Time Series Models; Chapter 24: Bioconductor; 24.1 An Example; 24.2 Key Bioconductor Packages; 24.3 Data Structures; 24.4 Where to Go Next; R Reference; base; boot; class; cluster; codetools; foreign; grDevices; graphics; grid; KernSmooth; lattice; MASS; methods; mgcv; nlme; nnet; rpart; spatial; splines; stats; stats4; survival; tcltk; tools; utils; Bibliography; Colophhhhhhon;

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. He is the inventor of several patents for computer security and cryptography, and the author of Baseball Hacks and R in a Nutshell.

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Sort by: Showing all of 7 Customer Reviews
  • Anonymous

    Posted January 26, 2010

    Great

    This book is great for any student, professional, or scholar who is starting out in R or is an intermediate R user who wants to know more. Joseph Adler does a great overview of what there is to offer. I used Stata for more than 5 years and finally made the switch. This book helped me realize how powerful R really is.

    I would not recommend this book to general readers or to R experts. The only place I did not give 5 stars is "General Readers". This book gives more details than a casual R user would need. Note that this book is not as in-depth as you could find for R. For example, Software for Data Analysis: Programming with R (Statistics and Computing) by Chambers is incredible if you want to know everything about R and get great programming intuition.

    For the complete beginners, I would recommend you just go to <a href="http://www.google.com">google</a> and search for material on R. There is also a website specialized in searching for R (because it is difficult to search for a letter): http://www.rseek.org. And of course there are great manuals at the home page of R: www.r-project.org

    2 out of 2 people found this review helpful.

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  • Anonymous

    Posted December 6, 2011

    R in a Nutshell gets you started

    This book has both tutorial information and reference material. Like other O'Reilly in a Nutshell volumes, its purpose is to get you started and have a handy paper reference. While you can do both of these with various web sites, R in a Nutshell makes it convenient and assures a basic comprehensive coverage.

    1 out of 1 people found this review helpful.

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  • Posted July 18, 2011

    cheaper on amazon

    It's $9 cheaper on amazon for kindle than for the nook. Why?

    1 out of 1 people found this review helpful.

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  • Anonymous

    Posted March 2, 2010

    Statistics Using R.

    This book is very thorough and is very useful for anyone who enters into a profession in which math is required. Those who major in statistics should use R; thus, this book should be recommended. I hope in time 'R in a Nutshell' will still be accurate, as the R software is updated.

    KP in Michigan.

    1 out of 1 people found this review helpful.

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    Posted April 10, 2010

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