Free Trial

Safari Books Online is a digital library providing on-demand subscription access to thousands of learning resources.

Overview

R is one of the best tools available for data visualization and statistical computing, and this book is simply the best way to learn this open source language and environment. Practical and easy to read, R in a Nutshell demonstrates why R is increasingly popular for analyzing moderate-to-large data sets. Most books available on R are stiff and academic, but this Nutshell guide offers a readable overview of the language, and contains a reference for the most commonly used features.

  • Learn the basics of the R language, such as syntax, expressions, and more

  • Analyze statistics in R using statistical tests, modeling functions, and charts

  • Discover R's graphical capabilities, including basic R graphics and lattice graphics

Scientists, researchers, and students in a variety of disciplines -- from biology, chemistry, and physics to social sciences, engineering, and webinformatics for social networks, performance analysis, and more -- can perform complicated statistical analysis in minutes that would take hours with Excel. R in a Nutshell shows you how.

Subscriber Reviews

Average Rating: 3.6 out of 5 rating Based on 5 Ratings

"Good introduction to R + reference..." - by Alex Ott on 24-AUG-2012
Reviewer Rating: 1 star rating2 star rating3 star rating4 star rating5 star rating
Good introduction to R + reference...
Report as Inappropriate

"A good introduction and reference" - by lotterblad on 24-MAY-2012
Reviewer Rating: 1 star rating2 star rating3 star rating4 star rating5 star rating
Whether you're experienced with an existing software package(like Matlab or SAS) Joseph Adler's R in Nutshell provides an excellent introduction and reference guide to R.

I mostly use R for research work and thus needed to know, how do I get data in and out of R? How to I download packages and apply functions? How do I create and use objects in R? R in a nutshell contained helpful concise guides that answered each of these questions.

The author has written a package(nutshell) with included examples, making it easy to test the code examples.

The latter chapters I'm referring back to now as I'm getting more into the machine learning side of R. Overall, I'd recommend this book to those just getting started or transitioning to R.  

Report as Inappropriate

Table of Contents

 

Extras

The publisher has provided additional content related to this title.


Description
Content

Visit the catalog page for R in a Nutshell

  • Catalog Page

Visit the errata page for R in a Nutshell

  • Errata

Download the supplemental electronic content for R in a Nutshell

  • Supplemental Content