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R is an open-source programming language designed for data science and statistics. It’s a powerful tool for working with data, and its documentation and supportive community offer helpful resources for new programmers.
For R, the basic reference is The New S Language: A Programming Environment for Data Analysis and Graphics by Richard A. Becker, John M. Chambers and Allan R. Wilks. The new features of the 1991 release of S are covered in Statistical Models in S edited by John
In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language.
Updated Oct 2023 · 18 min read. R is a statistical programming tool that’s uniquely equipped to handle data, and lots of it. Wrangling mass amounts of information and producing publication-ready graphics and visualizations is easy with R. So are all sorts of data analysis, mining, and modeling tasks.
When working in the data science field you will definitely become acquainted with the R language and the role it plays in data analysis. This course introduces you to the basics of the R language such as data types, techniques for manipulation, and how to implement fundamental programming tasks.
Jun 6, 2019 · Get started. ADVERTISEMENT. Learn the R programming language in this course from Barton Poulson of datalab.cc [https://datalab.cc/]. This is a hands-on overview of the statistical programming language R, one of the most important tools in data science. The course covers: * Installing R * RStudio * Packages *
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.
