R: The R Project for Statistical Computing
R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS. To download R, please choose your preferred CRAN mirror.
R (programming language) - Wikipedia
R is a programming language for statistical computing and data visualization. It has been adopted in the fields of data mining, bioinformatics, and data analysis. [9] The core R language is augmented by a large number of extension packages, containing reusable code, documentation, and sample data. R software is open-source and free software.
R: What is R? - The R Project for Statistical Computing
a well-developed, simple and effective programming language which includes conditionals, loops, user-defined recursive functions and input and output facilities.
R-4.4.2 for Windows - The Comprehensive R Archive Network
Download R-4.4.2 for Windows (83 megabytes, 64 bit) README on the Windows binary distribution. New features in this version. This build requires UCRT, which is part of Windows since Windows 10 and Windows Server 2016. On older systems, UCRT has to be installed manually from here.
R Tutorial - W3Schools
R is a programming language. R is often used for statistical computing and graphical presentation to analyze and visualize data. Start learning R now » Examples in Each Chapter. With our "Try it Yourself" editor, you can edit R code and view the result. Example. How to output some text, and how to do a simple calculation in R: "Hello World!" 5 + 5.
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An Introduction to R
a well developed, simple and effective programming language (called ‘S’) which includes conditionals, loops, user defined recursive functions and input and output facilities. (Indeed most of the system supplied functions are themselves written in the S language.)
R Programming Course (Johns Hopkins University) | Coursera
Learn R programming and effective data analysis in this Johns Hopkins University course on Coursera. Install and configure R, explore programming concepts, read data, access packages, write functions, debug, profile code, and organize/comment code with practical examples.