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  1. Feb 29, 2024 · R is a free software environment for statistical computing and graphics that runs on various platforms. Learn how to download, install, and use R, and get the latest news and updates on R releases, events, and packages.

    • The R Journal: Overview

      The R Journal is the peer-reviewed, open-access scientific...

    • Documentation

      Documentation Document Collections, Journals and...

    • Mailing Lists

      Mailing Lists. Please read the instructions below and the...

    • Windows - R

      Download R-4.4.1 for Windows (82 megabytes, 64 bit) README...

    • Getting Help

      The help() function and ? help operator in R provide access...

    • Cran

      R is ‘GNU S’, a freely available language and environment...

    • FAQs

      R has three collections of answers to frequently asked...

    • Books

      Books related to R. NOTE: modifications to this page have...

  2. R is a free software project that provides a wide range of statistical and graphical techniques, similar to the S language and environment. R is highly extensible, user-friendly and runs on various platforms, including Windows, MacOS and UNIX.

  3. 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. 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.

  4. Download R-4.4.1 for Windows (82 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.

  5. R is a free and open source language and environment for statistical computing and graphics. Download R for various platforms, browse contributed packages, read the R Journal, and learn more about R and CRAN.

  6. R is an environment designed for data science with a rich ecosystem of tools and libraries. Find your way to R with three tracks based on your experience level: beginners, intermediates, and experts.

  7. Learn how to use R's built-in help system, search for functions and objects, and find resources on the internet. This page covers documentation, vignettes, demos, FAQs, and more.

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