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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)
- What Is R Programming? Definition, Use Cases and FAQ
R is a free, open-source programming language tailored for data visualization and statistical analysis Find out more about the R programming language below
- LEARN R [Introduction, Data Structures, Data . . . - R CODER
This course is a set of tutorials sorted by category in which you will learn all the basics (and some more advanced content) to handle the R programming language
- 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
- Learn R - Online R Programming Tutorial
Welcome to the learn-r org interactive R tutorial with Examples and Exercises If you want to learn R for statistics, data science or business analytics, either you are new to programming or an experienced programmer this tutorial will help you to learn the R Programming language fast and efficient
- What is R in Programming? (Definition, Uses, Difficulty) | Built In
R is a free, open-source programming language used for statistical analysis and data visualization Popular in data science, R offers powerful tools for modeling, plotting, and working with large data sets across research and industry
- RStudio Education
R is not just a programming language, but it is also an interactive ecosystem including a runtime, libraries, development environments, and extensions All these features help you think about problems as a data scientist, while supporting fluent interaction between your brain and the computer
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