R is an open-source statistical programming language based on Bell Labs’ S with an extremely wide number of tests and functions, including extensive graphics and PDF and PostScript output.
A simple graphic user interface is included for Mac users; R Commander can be installed using the built-in package installer running on X11, which means it uses an alien interface and has odd open/save dialogues.
R has a steep learning curvem but, as Ashish Ranpura wrote,
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. R has stood the test of time and is likely to continue to do so.
There is one significant caveat: R 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 R project home page (with download links).
There is a R for Mac Special Interest Group, called R-Sig-Mac. The group is implemented as an e-mail list. You can subscribe to the list or see the archives going to its official web page: https://www.stat.math.ethz.ch/mailman/listinfo/r-sig-mac
A number of free programs are essentially graphical front ends to R, most notably Jamovi, JASP, and PAST.
The S language itself was developed at Bell Labs from 1976 onwards; its first commercial version was published by StatSci (later MathSoft) in 1993.
R was begun by Robert Gentleman and Ross Ihaka of the University of Auckland. Documentation that compares R and S include the online supplement to Venables and Ripley (1999) and the published text of Venables and Ripley (2000).
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