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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 free and open-source software distributed under the GNU General Public License [3][11] The language is implemented primarily in C, Fortran, and R itself Precompiled executables are available for the major operating systems (including Linux, MacOS, and Microsoft Windows)
R Programming Language - Introduction - GeeksforGeeks R is a programming language and software environment that has become the first choice for statistical computing and data analysis Developed in the early 1990s by Ross Ihaka and Robert Gentleman, R was built to simplify complex data manipulation and create clear, customizable visualizations
R | STAT ONLINE "R is a language and environment for statistical computing and graphics " "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 "
Learn R By Example We offer best R programming tutorials for people who want to learn R, fast We also provide examples for every single concept to make learning easy
Chapter 1 Introduction to R | Introduction to R R is a free and open source programming language widely used in academia, industry and government organisations for data science and machine learning R is well suited for interactive data analysis, visualization and modeling
The Comprehensive R Archive Network R is ‘GNU S’, a freely available language and environment for statistical computing and graphics which provides a wide variety of statistical and graphical techniques: linear and nonlinear modelling, statistical tests, time series analysis, classification, clustering, etc
Getting Help with R For information on how to ask questions, see, e g , the R mailing list posting guide, and the document about how to create reproducible examples for R on Stack Overflow