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R is a free statistical programming language based on the S and S/Plus programming languages. It provides libraries to solve common problems, and is completely extensible to implement any algorithm that you desire.
To date, few books have been written about R directly, so learning about R means following existing S and S/Plus documentation.
S has its origins in the pre-breakup AT&T Bell Labs. In its heydey, the statistics department employed John Tukey and Joseph Kruskal. The department lost some of its staff with the 1984 spin-off of the “Baby Bells” and the 1996 trivestiture of Lucent and AT&T.
Beginning in 1976, the S programming language was developed at Bell Labs by John Chambers and others. Version 1 required Honeywell mainframes, Version 2 (1980) added Unix support, Version 3 (1988) added functions and objects, and Version 4 (1998) added full support for object-oriented design.
Beginning in 1993, Bell Labs issued an exclusive license to StatSci (later MathSoft).S-Plus is Mathsoft’s commercial implementation of S, and the only way the language is available outside Lucent. The current implementation, S-Plus 2000, is offered in Windows, Unix and Linux implementations.
Numerous resources for S and S-Plus are available online, including
The following book is online
William N. Venables, Notes on S-PLUS: A Programming Environment for Data Analysis and Graphics, The University of Adelaide, vers 2.1, July 1992.
The following books have web pages of resources:
You can look for lists of books about S and S/Plus:
R begun by Robert Gentleman and Ross Ihaka of the University of Auckland. It is now an open source project staffed by volunteers from around the world.
The development is coordinated through the Comprehensive R Archive network, and full source code, binaries and documentation are available free at the CRAN web site. The web site also includes information on three R-related mailing lists.
Documentation that compares R and S include:
Adapted from the August 2000 Academy of Management workshop on stat packages, below is the compiled on how to use R to perform statistical analyses common in management research:
Base package commands:
Built-in packages
Contributed R packages and their capabilities:
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Originally prepared by Joel West of the UCI Graduate School of Management. Copyright © 2000-2001 Joel West, Copyright © 2005-2008 Allpar, LLC. All rights reserved. Organizational change and organizational development articles ... Macintosh statistics software