For newcomers to R who have at least a basic background in the principles of statistical analysis, John Maindonald has contributed an introductory guide to R: Using R for Data Analysis and Graphics. It uses a series of data sets and example R code to take the beginning user through launching R (on a Windows system; installing R is not covered), executing simple commands at the command-line, understanding objects and R function calls, graphics, and some simple statistical modeling techniques. Later chapters do touch on some more advanced modeling methods and how to program your own functions, but these sections can safely be ignored by the beginning R user.
The datasets used in the examples, and the scripts used to generate each analysis and graphic are available for download. (The document was last updated in January 2008, so there might be slight differences in the output in newer versions of R.)
You might also want to check out the book Data Analysis and Graphics using R: An Example-Based Approach by John Maindonald and John Braun, available from Cambridge University Press (UK) and from Amazon (US). The book covers similar introductory material but with over 500 pages has greatly expanded coverage and examples of the various types of statistical models you can fit using R. The datasets and code used for each chapter are also available.
J H Maindonald: Using R for Data Analysis and Graphics: Introduction, Code and Commentary (PDF, 96 pages)
How do I extract only positive values of a time series with negative and positive real numbers?
Posted by: Ram Ramaiah | October 20, 2012 at 11:53