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This is the only introduction you'll need to start programming in R, the open-source language that is free to download, and lets you adapt the source code for your own requirements. Co-written by one of the R Core Development Team, and by an established R author, this book comes with real R code that complies with the standards of the language. Unlike other introductory books on the ground-breaking R system, this book emphasizes programming, including the principles that apply to most computing languages, and techniques used to develop more complex projects. Learning the language is made easier by the frequent exercises and end-of-chapter reviews that help you progress confidently through the book. Solutions, datasets and any errata will be available from the book's web site. The many examples, all from real applications, make it particularly useful for anyone working in practical data analysis.Read more
- First book to teach basic computer programming in R, the language of choice for statistics and data analysis
- Authors are recognized and trusted: John Braun is co-author of the successful book Data Analysis and Graphics Using R; Duncan Murdoch is a member of the R Core Development Team
- End-of-chapter review questions plus over 150 exercises, data sets and solutions all available on the web
Reviews & endorsements
"While it is rare to see in a book, denseness does not have to be difficult and this book is an example of that. The authors are terse and effective as they clearly demonstrate how to use the R package. If you lack the budget for the purchase of a commercial computational mathematics package, then R with this textbook provides a very low cost alternative for many classes."
Charles Ashbacher, Journal of Recreational MathematicsSee more reviews
" a useful introductory text..."
Andrew Schaffner, The American Statistician
"As an R novice, I appreciated the explanations. Several times, I reacted with 'Oh, that's how it is supposed to be done.' ... I like this book and I learned a lot. I am convinced that most readers (including regular R users and mature statisticians) will learn something useful from this book. Again, it is not a book for learning statistical data analysis in R, but it is the right book for a statistician to learn the structure of R, and it is a good book to study before (or after) learning data analysis. I highly recommend this book."
Myron Hlynka, Technometrics
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- Date Published: January 2008
- format: Paperback
- isbn: 9780521694247
- length: 172 pages
- dimensions: 246 x 189 x 10 mm
- weight: 0.392kg
- contains: 39 b/w illus. 160 exercises
- availability: In stock
Table of Contents
1. Getting started
2. Introduction to the R language
3. Programming statistical graphics
4. Programming with R
6. Computational linear algebra
7. Numerical optimization
Appendix. Review of random variables and distributions