A First Course in Statistical Programming with R (2nd ed.)

by W. John Braun, Duncan J. Murdoch

Subject categories
ISBNs
  • 9781107576469
  • 9781316715802
  • 9781316714829
This new color edition of Braun and Murdoch's bestselling textbook integrates use of the RStudio platform and adds discussion of newer graphics systems, extensive exploration of Markov chain Monte Carlo, expert advice on common error messages, motivating applications of matrix decompositions, and numerous new examples and exercises. This is the only introduction needed to start programming in R, the computing standard for analyzing data. Co-written by an R core team member and 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 R system, this book emphasizes programming, including the principles that apply to most computing languages, and techniques used to develop more complex projects. Solutions, datasets, and any errata are available from the book's website. The many examples, all from real applications, make it particularly useful for anyone working in practical data analysis.
  • Cambridge University Press; July 2016
  • ISBN: 9781316715802
  • Edition: 2
  • Read online, or download in secure PDF or secure ePub format
  • Title: A First Course in Statistical Programming with R
  • Author: W. John Braun; Duncan J. Murdoch
  • Imprint: Cambridge University Press
Subject categories
ISBNs
  • 9781107576469
  • 9781316715802
  • 9781316714829

In The Press

'This book should be especially useful for those without any prior programming background. The core programming material, such as loops and functions, is postponed to Chapter 4, allowing the student to first become comfortable with R in a broader manner. The placement of Chapter 3, on graphical methods, is particularly helpful in this regard, and is very motivating. The book is written by two recognized experts in the R language, so the reader attains the benefit of being taught by the 'insiders'.' Norm Matloff, University of California, Davis