R free download for Mac

R for Mac

16 February 2021

Statistical computing and graphics.

What is R for Mac

R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. There are some important differences, but much code written for S runs unaltered under R.

R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible. The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity.

One of R's strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed. Great care has been taken over the defaults for the minor design choices in graphics, but the user retains full control.

What's new in R

Version 4.0.4:
New features:
  • File share/texmf/tex/latex/jss.cls has been updated to work with LaTeX versions since Oct 2020.
  • Unicode character width tables (as used by nchar(, type = "w")) have been updated to Unicode 12.1 by Brodie Gaslam (PR#17781), including many emoji.
  • The internal table for iswprint (used on Windows, macOS and AIX) has been updated to include many recent Unicode characters.
Installation on a unix-alike:
  • If an external BLAS is specified by --with-blas=foo or _via_ environment variable BLAS_LIBS is not found, this is now a configuration error. The previous behaviour was not clear from the documentation: it was to continue the search as if --with-blas=yes was specified.
Bug fixes:
  • all.equal(x,y) now "sees" the two different NAs in factors, thanks to Bill Dunlap and others in PR#17897.
  • (~ NULL)[1] and similar formula subsetting now works, thanks to a report and patch by Henrik Bengtsson in PR#17935. Additionally, subsetting leaving an empty formula now works too, thanks to suggestions by Suharto Anggono.
  • .traceback(n) keeps source references again, as before R 4.0.0, fixing a regression; introduced by the PR#17580, reported including two patch proposals by Brodie Gaslam.
  • unlist(plst, recursive=FALSE) no longer drops content for pairlists with list components, thanks to the report and patch by Suharto Anggono in PR#17950.
  • iconvlist() now also works on MUSL based (Linux) systems, from a report and patch suggestion by Wesley Chan in PR#17970.
  • round() and signif() no longer tolerate wrong argument names, notably in 1-argument calls; reported by Shane Mueller on R-devel (mailing list); later reported as PR#17976.
  • .Machine has longdouble.* elements only if capabilities("long.double") is true, as documented. (Previously they were included if the platform had long double identical to double, as ARM does.)
  • p.adjust(numeric(), n=0) now works, fixing PR#18002.
  • identical(x,y) no longer prints "Unknown Type .." for typeof(x) == "..." objects.
  • Fix (auto-)print()ing of named complex vectors, see PR#17868 and PR#18019.
  • all.equal(, ) now works, fixing PR#18029.
  • as.data.frame.list(L, row.names=NULL) now behaves in line with data.frame(), disregarding names of components of L, fixing PR#18034, reported by Kevin Tappe.
  • checkRdaFiles(ff)$version is now correct also when ff contains files of different versions, thanks to a report and patch from Sebastian Meyer in PR#18041.
  • macOS: Quartz device live drawing could fail (no plot is shown) if the system changes the drawing context after view update (often the case since macOS Big Sur). System log may show "CGContextDelegateCreateForContext: invalid context" error.
R for Mac Old Versions

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How would you rate R?
0.0
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Selasley
Selasley
Apr 25 2020
3.6.3
0.0
Apr 25 2020
0.0
Version: 3.6.3
Version 4.0.0 released today. Release notes here https://stat.ethz.ch/pipermail/r-announce/2020/000653.html
Hachepunto
Hachepunto
Jul 31 2015
3.2.1
5.0
Jul 31 2015
5.0
Version: 3.2.1
There's lots of software available for data analysis today: spreadsheets like Excel, batch-oriented procedure-based systems like SAS; point-and-click GUI-based systems like SPSS; data mining systems, and so on. What makes R different? R is free. As an open-source project, you can use R free of charge: no worries about subscription fees, license managers, or user limits. But just as importantly, R is open: you can inspect the code and tinker with it as much as you like (provided you respect the terms of the GNU General Public License version 2 under which it is distributed). Thousands of experts around the world have done just that, and their contributions benefit the millions of people who use R today. R is a language. In R, you do data analysis by writing functions and scripts, not by pointing and clicking. That may sound daunting, but it's an easy language to learn, and a very natural and expressive one for data analysis. But once you learn the language, there are many benefits. As an interactive language (as opposed to a data-in-data-out black-box procedures), R promotes experimentation and exploration, which improves data analysis and often leads to discoveries that wouldn't be made otherwise. A script documents all your work, from data access to reporting, and can instantly be re-run at any time. (This makes it much easier to update results when the data change.) Scripts also make it easy to automate a sequence of tasks that can be integrated into other processes. Many R users who have used other software report that they can do their data analyses in a fraction of the time. Graphics and data visualization. One of the design principles of R was that visualization of data through charts and graphs is an essential part of the data analysis process. As a result, it has excellent tools for creating graphics, from staples like bar charts and scatterplots to multi-panel Lattice charts to brand new graphics of your own devising. R's graphical system is heavily influenced by thought leaders in data visualization like Bill Cleveland and Edward Tufte, and as a result graphics based on R appear regularly in venues like the New York Times, the Economist, and the FlowingData blog. A flexible statistical analysis toolkit. All of the standard data analysis tools are built right into the R language: from accessing data in various formats, to data manipulation (transforms, merges, aggregations, etc.), to traditional and modern statistical models (regression, ANOVA, GLM, tree models, etc). All are included in an object-oriented framework that makes it easy to programatically extract out and combine just the information you need from the results, rather than having to cut-and-paste from a static report. Access to powerful, cutting-edge analytics. Leading academics and researches from around the world use R to develop the latest methods in statistics, machine learning, and predictive modeling. There are expansive, cutting-edge edge extensions to R in finance, genomics, and dozens of other fields. To date, more than 2000 packages extending the R language in every domain are available for free download, with more added every day. A robust, vibrant community. With thousands of contributors and more than two million users around the world, if you've got a question about R chances are, someone's answered it (or can). There's a wealth of community resources for R available on the Web, for help in just about every domain. Unlimited possibilities. With R, you're not restricted to choosing a pre-defined set of routines. You can use code contributed by others in the open-source community, or extend R with your own functions. And R is excellent for "mash-ups" with other applications: combine R with a MySQL database, an Apache web-server, and the Google Maps API and you've got yourself a real-time GIS analysis toolkit. That's just one big idea -- what's yours? source: http://www.inside-r.org/why-use-r
WooDMco
WooDMco
Jun 22 2015
3.2.1
0.0
Jun 22 2015
0.0
Version: 3.2.1
Today's download is for the SOURCE code, not the R.app application. You will need the developer tools to build the app.
buffonm1
buffonm1
May 5 2015
3.2.0
5.0
May 5 2015
5.0
Version: 3.2.0
Hey everyone, i have a problem. Just downloaded R, but this came up: You're using a non-UTF8 locale, therefore only ASCII characters will work. Does anyone know what i can do?
anonymous-hummingbird-1667
anonymous-hummingbird-1667
Apr 7 2015
3.1.3
5.0
Apr 7 2015
5.0
Version: 3.1.3
You need to invest time in learning R, but then once you're really into it there's no way you can go back to SPSS etc. An IDE (e.g. RStudio) is highly recommended though.
Chuckk
Chuckk
Feb 8 2015
3.1.2
5.0
Feb 8 2015
5.0
Version: 3.1.2
cross platform capability, extremely powerful, well supported. Learning curve is a bit steep but well worth it.
Tobit
Tobit
Apr 12 2014
3.1.0
4.5
Apr 12 2014
4.5
Version: 3.1.0
Great software, but take care with "Snow Leopard" download link !! It exists a "Mavericks" version too ;-)
Dorkypants
Dorkypants
Apr 12 2014
3.1.0
0.0
Apr 12 2014
0.0
Version: 3.1.0
Package installer fails on my 2009 MacBook Pro 13" running Snow Leopard 10.6.8 with all available Software Updates installed
Danlfsmith
Danlfsmith
Aug 3 2012
2.15.1
5.0
Aug 3 2012
5.0
Version: 2.15.1
R has revolutionized statistical computing over the last 10 years. Every student of statistics or science today probably needs to learn R. It can be used for amazingly complex analysis, as well as the simple stuff. It has a reputation for being hard to learn, but that's mainly because it's so powerful and flexible. Fortunately there are many good books available to teach R. I like "Introductory Statistics with R," by Peter Dalgaard.
biop090
biop090
Jan 5 2012
2.14.1
5.0
Jan 5 2012
5.0
Version: 2.14.1
GREAT!
Free

4.7

App requirements: 
  • Intel 64
  • OS X 10.11.0 or later
License: 
FreeAbsolutely Free

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