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Home > Catalogue > A First Course in Statistical Programming with R
A First Course in Statistical Programming with R


  • 39 b/w illus. 160 exercises
  • Page extent: 172 pages
  • Size: 246 x 189 mm
  • Weight: 0.392 kg
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 (ISBN-13: 9780521694247)

  • There was also a Hardback of this title but it is no longer available | Adobe eBook
  • Published December 2007

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 (Stock level updated: 12:22 GMT, 26 November 2015)


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.

• 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


1. Getting started; 2. Introduction to the R language; 3. Programming statistical graphics; 4. Programming with R; 5. Simulation; 6. Computational linear algebra; 7. Numerical optimization; Appendix. Review of random variables and distributions; Index.


'… with this book, you can be up and running, doing very advanced work with R in a matter of minutes. Using a series of code examples, the authors take you through many of the basic capabilities of the package. All that is needed to follow the examples is a basic understanding of control constructs such as the if-then, loops and functions as well as knowledge of the underlying mathematics.' Charles Ashbacher, Journal of Recreational Mathematics

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