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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 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.
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.
Feb 12, 2024 · R is a free, open-source programming language, meaning anyone can use, modify, and distribute it. It was initially written by Ross Ihaka and Robert Gentleman (also known as R&R) of the University of Auckland’s Statistics Department.
R is a popular programming language that allows people to adeptly handle mass amounts of data, generate publication-quality visualizations, and perform a range of statistical and analytic computing tasks. Used in fields including data science, finance, academia, and more, R is powerful, flexible, and extensible.
This is an introduction to R (“GNU S”), a language and environment for statistical computing and graphics. R is similar to the award-winning 1 S system, which was developed at Bell Laboratories by John Chambers et al.
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.
R is a free, open-source programming language designed specifically for data mining, statistical analysis, data visualization, and machine learning. R’s capacity for visualizing data makes it popular with data scientists and data analysts.
What is R? R vs Python. Popular R Tutorials. Linear Regression in R. Logistic regression in R. Principal Component Analysis in R. Histograms in R. Hierarchical Clustering in R. Decision Trees in R. Importing Data into R. Contingency Tables in R. Easily search the documentation for every version of every R package on CRAN and Bioconductor.
