A First Course in Statistical Programming with R
Nonfiction, Computers, Advanced Computing, Natural Language Processing, Science & Nature, Mathematics, Statistics
| Author: | W. John Braun, Duncan J. Murdoch | ISBN: | 9781316099605 |
| Publisher: | Cambridge University Press | Publication: | December 13, 2007 |
| Imprint: | Cambridge University Press | Language: | English |
| Author: | W. John Braun, Duncan J. Murdoch |
| ISBN: | 9781316099605 |
| Publisher: | Cambridge University Press |
| Publication: | December 13, 2007 |
| Imprint: | Cambridge University Press |
| Language: | English |
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.
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.
