- Roblox
Roblox is the ultimate virtual universe that lets you create, share experiences with friends, and be anything you can imagine Join millions of people and discover an infinite variety of immersive experiences created by a global community!
- 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 Tutorial - W3Schools
R is a programming language R is often used for statistical computing and graphical presentation to analyze and visualize data Tip: Sign in to track your progress - it's free With our "Try it Yourself" editor, you can edit R code and view the result How to output some text, and how to do a simple calculation in R: "Hello World!" Result:
- Learn R - Codecademy
R is a widely used programming language that works well with data It’s a great option for statistical analysis, and has an active development community that’s constantly releasing new packages, making R code even easier to use
- 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
- 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
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