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R in a Nutshell: A Desktop Quick Reference [Paperback]

Joseph Adler

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R in a Nutshell R in a Nutshell 4.0 out of 5 stars (1)
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Book Description

Jan 11 2010 In a Nutshell (O'Reilly)

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."


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R in a Nutshell: A Desktop Quick Reference + R Cookbook + A Beginner's Guide to R
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Product Description

About 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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Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
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Amazon.com: 3.9 out of 5 stars  27 reviews
72 of 74 people found the following review helpful
5.0 out of 5 stars Gateway into the world of R April 14 2010
By Tony DaBoney - Published on Amazon.com
Format:Paperback|Amazon Verified Purchase
'R in a Nutshell' is the essential introductory book on R. Do not try to learn R without it.

I made two attempts to learn R before purchasing this book. In both previous attempts, I had to abort and use another tool to solve my problem because it was taking me too long to accomplish very simple things in R.

The reason R is hard to learn is that its documentation is organized for statisticians that already know R, but have forgotten a detail or two. There are a few other books on learning R, but they are setup like a college course - complete the entire book and THEN you can actually accomplish something.

R in a Nutshell allows you to get working immediately. Simply lookup what you need to do. The firsts thing I did was load a file and make a histogram. I found that stuff in the section on "Loading Data" and the section on charts. In no time I was making stacked area charts for cohorts. Now R is an essential tool for me - and I haven't even taken the time to learn it well! With this book, I don't have to. I can learn as I go. So I actually use R.

Do not R without it.
66 of 71 people found the following review helpful
5.0 out of 5 stars Useful and surprisingly engaging Jan 14 2010
By Gimpel the Fool - Published on Amazon.com
Format:Paperback
Back in school, I was introduced to using SPSS for use in statistical analysis. While I liked SPSS, it was too expensive for me to procure a copy for my own personal use. A friend suggested that I try R. I was a little nervous about R, because being more enthusiastic about than talented with mathematics, and I was most comfortable with a point and click program. So, before I began, I bought "R in a Nutshell" to learn more. I'm glad that I did.

Adler's book begins with a basic tutorial for R and an introduction to R language. It explains how to use R to draw graphs, statistical analysis and even some bio stuff. All I needed to do was to load in my data, draw a couple charts and compute some t tests and chi-squared statistics.

The book was great, multi-faceted as a teaching tool, and - unexpectedly (and atypically for such works) - entertaining to read. I'm looking forward to using R next time I need to fit a regression model, or do factor analysis. The rare mathematics tutorial that will engage academics, financial traders and baseball stat wonks alike. Nice job.
36 of 39 people found the following review helpful
3.0 out of 5 stars in purgatory between tutorial and reference Jun 4 2010
By Joseph Clark - Published on Amazon.com
Format:Paperback
I've just gotten the book, my first resource for learning R, and I find it moderately helpful but in some ways frustrating. O'Reilly's books usually take the form of either a progressive set of lessons in a language (like the famous "Learning Perl") or as an easily navigable reference book (like "Java in a Nutshell"). This book places itself somewhere in the middle. It begins with a fairly limited tutorial that covers basics of the scripting language but doesn't get into what a researcher would really use R for: importing data and running an analysis. This is complemented by a glossary of functions, but it contains little detail (not even the function's required arguments are listed) and they are not in anything like alphabetical order, instead grouped by the several "packages" that contain them. I went looking for the "standard deviation" function and there was no easy way to find it in the glossary, nor was the book's index any help -- it indexes the chapters but not the language reference.

Given the relative dearth of books available, this may or may not be the best introduction to the language available, but it leaves me wanting two better books: one for learning more about R, and one for a better reference.

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