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R is a comprehensive statistical programming language that is cooperatively developed on the Internet as an open source project. It is often referred to as the “GNU S,” because it almost completely emulates the S programming language. It has packages to do regression, ANOVA, general linear models, hazard models and structural equations.
Ashish Ranpura wrote:
Last week I finally put R through its paces on two recent experiments from our lab. It performed spectacularly. It's pretty easy to learn using online tutorials, in particular John Verzani's tutorial which is a course in introductory statistics using R.
The highlight: figuring out the 15 or so commands to import, parse, slice and graph a 3-way comparison of control subjects using a scatterplot and a violin plot. Then using BBEdit to search and replace the word "control" with my two experimental conditions, pasting that back into R, and generating a report with all 6 graphs in about 3 keystrokes! Now that's how a program ought to work.
But the major advantages of R are that it is absolutely cross-platform (Linux, MacOS, Windows) and that it's open source. You've a good chance of accessing your data 10 years from now, which I wouldn't say with the commercial packages. The user base is large, active, and productive. The S language on which it's based is a well-accepted standard in statistics, and has been since its development in the early 1980s. R has stood the test of time and is likely to continue to do so.
There is one significant caveat: R is not a mouse lover's program. It is relentlessly command-line driven, and even the graphs cannot be edited with mouse clicks. It's trivial to take the PDF graphs into Illustrator, though, so this limitation hasn't been a problem for me.
Some resources include:
The current version is 2.12 and includes Tiger support - see http://www.r-project.org/ for more information.
There are currently several version of R available for Mac users.
If you are not familiar with the differences between Carbon and Cocoa native mode software for OS X, or OS X and Darwin, see the OS X architecture background report.
R has been ported to the Mac OS by Stefano Iacus of the University degli Studi di Milano. The original version was designed for OS 8/9, but from version 1.2.3 onward the software is fully carbonized. This means that it runs native under OS X with the same menus as under OS 8/9, but with Apple’s “Aqua” user interface.
See these web pages for more information:
R was also ported to Mac OS X using its UNIX application programming interfaces. The work was done by Jan de Leeuw, Professor of Statistics at UCLA. See the initial announcement of its features for more details. It can be run on OS X using one of three different ways:
The software was developed for use under OS X 10.1.x. However, it uses the application programming interfaces of the “Darwin” portion of OS X, and thus should also work under Darwin 1.4.
For more information, see
The R sources were originally designed for Unix, and have been ported to many version of Linux. Most of these version of Linux run on Intel-based systems.
The R for LinuxPPC port is compiled by Alex Buerkle of the University of Wisconsin, Eau Claire.
There is a R for Mac Special Interest Group, called R-Sig-Mac. The group is implemented as an e-mail list. The list exists to “exchange ideas, impressions, give suggestions etc. on the portings of R for MacOS and MacOS X.”
You can subscribe to the list going to its official web page:
http://www.stat.math.ethz.ch/mailman/listinfo/r-sig-mac
and also find the archives of back articles.
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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