R
R
4.1.1
4.8
0.0
R free download for Mac

R for Mac

13 August 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 4.1.1:
New features:
  • require(pkg, quietly = TRUE) is quieter and in particular does not warn if the package is not found.
Deprecated and defunct:
  • Use of ftp:// URIs should be regarded as deprecated, with on-going support confined to method = "libcurl" and not routinely tested. (Nowadays no major browser supports them.)
  • The non-default method = "internal" is deprecated for http:// and ftp:// URIs for both download.file and url.
  • On Windows, method = "wininet" is deprecated for http://, https:// and ftp:// URIs for both download.file and url. (A warning is only given for ftp://.)
  • For ftp:// URIs the default method is now "libcurl" if available (which it is on CRAN builds).
  • method = "wininet" remains the default for http:// and https:// URIs but if libcurl is available, using method = "libcurl" is preferred.
Installation:
  • make check now works also without a LaTeX installation. (Thanks to Sebastian Meyer's PR#18103.)
Bug fixes:
  • make check-devel works again in an R build configured with --without-recommended-packages.
  • qnbinom(p, size, mu) for large size/mu is correct now in a range of cases (PR#18095); similarly for the (size, prob) parametrization of the negative binomial. Also qpois() and qbinom() are better and or faster for extreme cases. The underlying C code has been modularized and is common to all four cases of discrete distributions.
  • gap.axis is now part of the axis() arguments which are passed from bxp(), and hence boxplot(). (Thanks to Martin Smith's report and suggestions in PR#18109.)
  • .First and .Last can again be set from the site profile.
  • seq.int(from, to, *) and seq.default(..) now work better in large range cases where from-to is infinite where the two boundaries are finite.
  • all.equal(x,y) now returns TRUE correctly also when several entries of abs(x) and abs(y) are close to .Machine$double.xmax, the largest finite numeric.
  • model.frame() now clears the object bit when removing the class attribute of a value via na.action (PR#18100).
  • charClass() now works with multi-character strings on Windows (PR#18104, fixed by Bill Dunlap).
  • encodeString() on Solaris now works again in Latin-1 encoding on characters represented differently in UTF-8. Support for surrogate pairs on Solaris has been improved.
  • file.show() on Windows now works with non-ASCII path names representable in the current native encoding (PR#18132).
  • Embedded R on Windows can now find R home directory via the registry even when installed only for the current user (PR#18135).
  • pretty(x) with finite x now returns finite values also in the case where the extreme x values are close in size to the maximal representable number .Machine$double.xmax.
  • Also, it's been tweaked for very small ranges and when a boundary is close (or equal) to zero; e.g., pretty(c(0,1e-317)) no longer has negative numbers, currently still warning about a very small range, and pretty(2^-(1024 - 2^-1/(c(24,10)))) is more accurate.
  • The error message for not finding vignette files when weaving has correct file sizes now. (Thanks to Sebastian Meyer's PR#18154.)
  • dnbinom(20, , 1) now correctly gives 0, and similar cases are more accurate with underflow precaution. (Reported by Francisco Vera Alcivar in PR#18072.)
R for Mac Old Versions
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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!
Pedroj
Pedroj
Sep 26 2010
2.11.1
5.0
Sep 26 2010
5.0
Version: 2.11.1
R is the tool for choice for serious statistical analysis. It's not an easy platform, however, and learning takes some time. The good side is how powerful it is for *any* type of analysis, data, or problem. The help support is very good and user forums are very active and helpful. This is not the package of choice if you are doing sporadic data analysis, but I'd recommend it to anyone seriously involved in statistical analysis. If you are just starting with statistics and plan to keep doing data analysis- go for it. If you are using other packages and statistical analysis is a major part of your study, go for it. No other package offers the versatility and support R has. If the command line mode is really intimidating to you, you can use the R-Commander GUI (just install the Rcmdr package), but the real power of R lies in its command-line. You can run R with the binary cocoa application, from the Terminal, within emacs, or within TextMate.
Joachimr
Joachimr
Mar 24 2009
2.8.1
5.0
Mar 24 2009
5.0
Version: 2.8.1
Top-notch statistical analysis software for an unbeatable price. You do have to invest some time to learn how to work it, but that's well worth the price of admission. Many statistical tools become available on this platform way before others (much more costly ones). It is supported by a wide, global user and programmer base. Get yourself a book to learn how to use it if you are not the adventurous or "I'd rather do this with a command-line" type.
Umijin
Umijin
May 25 2006
2.3
0.0
May 25 2006
0.0
Version: 2.3
I downloaded the package, ran the installer and after starting R, the app remains in 'loading R' status interminably. I have to 'force quit' R to get out of it. I'm running a 20" G5 iMac with OSX10.4.6 Any idea of what the problem is?
Guest
Guest
Oct 22 2004
2.0.0
4.3
Oct 22 2004
4.3
Version: 2.0.0
A significant upgrade. The interface is now a lot less baffling. The most immediately-visible changes affect the ease with which you can see what is in your workspace and how easily you can access help files. R is powerful, but has hitherto been daunting in its minimalist interface. This is still a package for the professional, but is now going to be a lot easier to get to grips with.
Guest
Guest
Oct 22 2004
2.0.0
4.3
Oct 22 2004
4.3
Version: 2.0.0
One of the most robust and powerful statistical package that just happens to be free, as well. Most of its power comes from command line interface, but the object browsers can't hurt. Is it just me or it tends to run a lot faster when run directly from terminal app?
Free
4.8
0.0
App requirements: 
  • Intel 64
  • OS X 10.11.0 or later
  • X11 system manager (optional, now requires XQuartz)
  • GNU g77 compiler and tcltk libraries included with the installer
License: 
FreeAbsolutely Free
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