- Paperback: 172 pages
- Publisher: Cambridge University Press; 1 edition (January 28, 2008)
- Language: English
- ISBN-10: 0521694248
- ISBN-13: 978-0521694247
- Product Dimensions: 7.4 x 0.4 x 9.7 inches
- Shipping Weight: 14.6 ounces (View shipping rates and policies)
- Average Customer Review: 11 customer reviews
- Amazon Best Sellers Rank: #643,128 in Books (See Top 100 in Books)
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A First Course in Statistical Programming with R 1st Edition
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"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 Mathematics
" 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
The only introduction you'll need to start programming in R. Co-written by one of the R Core Development Team, and by an established R author, the book includes real R code that complies with the standards of the language. Exercises and end-of-chapter reviews help you progress confidently through the book.
Top customer reviews
Recognize that R is not just a programming language, not in the sense of Python or Ruby or C. It is a universe. In addition to the capability in the base language, the availability of hundreds of sophisticated packages extends its capability to all kinds of terrains, from the traditional and statistical, to GIS, spatial, image-based, and nearly research edges. Mastery of those packages would take a lifetime. There are new ones every month.
But these packages are not what the average user needs or wants. What the average user needs or wants is a gentle introduction, how to install R, how to use it for common things, getting data in and out, some graphs, some basic statistical notions. Alas, until recently, most R books were sophisticated presentations, ones giving terse, in depth illustrations of R's uses for statistics and analysis. It was difficult to find discussions on the core language, and most of those went back to S+, and Chambers. Admittedly, there are detailed discussions of these as PDF documents with installations, but these may not be reachable by the casual user.
Fortunately, today we have at one end of the beginners' path, the Venables and Smith AN INTRODUCTION TO R. That text is also available online, and was part of some installations of R, at least on Windows. At the other end of the beginners' path is Rizzo's STATISTICAL COMPUTING WITH R, a book on introductory statistics using R for illustration. And, in the middle of the path, there's this text, Braun and Murdoch's A FIRST COURSE. It's fine. It won't let you down. You won't learn how to do projection pursuit regression with R from it. But, then, many people don't need that.