With thousands of contributors and more than two million users around the world, if youve got a question about R chances are, someones answered it (or can).Desktop Sign in Create account Categories Desktop R 4.0.2 4.7 Download ( 88.1 MB ) Home Education Mathematics R R 4.0.2 4.0.2 See all Versions 25 June 2020 Statistical computing and graphics.Follow this app Developer website Overview 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 ATT, now Lucent Technologies) by John Chambers and colleagues. R-Studio Versions Code Written ForThere are some important differences, but much code written for S runs unaltered under R. 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. Great care has been taken over the defaults for the minor design choices in graphics, but the user retains full control. R-Studio Versions Mac Offers FromSubscribe for our newsletter with best Mac offers from MacUpdate. Subscribe How would you rate R app Post review 15 Reviews of R 5 anonymous-hummingbird-1667 07 April 2015 Version: 3.1.3 Most helpful You need to invest time in learning R, but then once youre really into it theres no way you can go back to SPSS etc. An IDE (e.g. RStudio) is highly recommended though. Selasley 25 April 2020 Version: 3.6.3 Version 4.0.0 released today. R-Studio Versions Free Of ChargeR 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 its an easy language to learn, and a very natural and expressive one for data analysis. 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 wouldnt be made otherwise. A script documents all your work, from data access to reporting, and can instantly be re-run at any time. Many R users who have used other software report that they can do their data analyses in a fraction of the time. 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. Rs 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. 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. 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.
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