R

https://www.r-project.org
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 If you have questions about R like how to download and install the software or what the license terms are please read our

https://cran.r-project.org/bin/windows/base
The R project for statistical computing R 4 3 2 for Windows Download R 4 3 2 for Windows 79 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

https://en.wikipedia.org/wiki/R_(programming_language)
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 8 The core R language is augmented by a large number of extension packages containing reusable code documentation and sample data

https://www.youtube.com/watch?v=_V8eKsto3Ug
0 00 2 10 39 Learn the R programming language in this tutorial course This is a hands on overview of the statistical programming language R one of the most important to

https://www.r-project.org/about.html
R is a language and environment for statistical computing and graphics It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories formerly AT T now Lucent Technologies by John Chambers and colleagues

https://cran.r-project.org/doc/manuals/r-release/R-intro.pdf
R is an integrated suite of software facilities for data manipulation calculation and graphical display Among other things it has an effective data handling and storage facility a suite of operators for calculations on arrays in particular matrices a large coherent integrated collection of intermediate tools for data analysis

https://cran.r-project.org
What are R and CRAN 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

https://www.coursera.org/learn/r-programming
The course covers practical issues in statistical computing which includes programming in R reading data into R accessing R packages writing R functions debugging profiling R code and organizing and commenting R code

https://www.r-project.org/help.html
The help function and help operator in R provide access to the documentation pages for R functions data sets and other objects both for packages in the standard R distribution and for contributed packages