R in a Nutshell: A Desktop Quick Reference Review

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(More customer reviews)'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.

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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 Computing

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

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Damned Lies and Statistics: Untangling Numbers from the Media, Politicians, and Activists Review

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(More customer reviews)Are ten percent of Americans gay? Is the white male in the work force rapidly becoming a minority? Are 150,000 young American women dying each year from anorexia?
Joel Best clearly answers "no" to each of these three questions and, more importantly, shows why many people would say "yes". His point is that descriptive statistics are the product of a social activity, not just a representation of society. Social advocacy causes people to collect the data that they feel will best support their preconceived notions: They talk to unrepresentative groups. They start to collect new measures and then wonder why the "statistics" have grown since ten years earlier (when they weren't much -- if at all -- measured). They multiply erroneous assumptions. They mutate data. And the press and other publications carry the mutations forward.
This book offers plenty of illustrations of intentions run amok. Many of the reports provide useful information for a classroom lecture on the need to discern if a person is "speaking rot", as Harold Macmillan once said was the primary purpose of an education.
A good, crisp 171 pages in length, it is absent discussion of the more difficult inferential statistics and, as a result, it is easy to understand by the lay person.

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