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,
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The goal of “R for Data Science” is to help you learn the most important tools in R that will allow you to do data science efficiently and reproducibly, and to have some fun along the way 😃.
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Most R novices will start with the introductory session in Appendix A. This should give some familiarity with the style of R sessions and more importantly some instant feedback on what actually happens.
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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
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R is a popular programming language used for statistical computing and graphical presentation. Its most common use is to analyze and visualize data. Why Use R? This tutorial will teach you the basics of
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An introduction to R, discuss on R installation, R session, variable assignment, applying functions, inline comments, installing add-on packages, R help and documentation.
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The R statistical environment works for most standard operating systems (i.e., Mac, Windows, Linux), but certain features (particularly related to graphics and parallel computing) are only available on
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An Introduction to R Alex Douglas, Deon Roos, Francesca Mancini, Ana Couto & David Lusseau January 15, 2026
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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
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