rStatistics

Mastering Statistical Computing

Learn R Programming

R is a programming language for statistical computing and graphics supported by the R Core Team and the R Foundation for Statistical Computing. Created by statisticians Ross Ihaka and Robert Gentleman, R is used among data miners, bioinformaticians and statisticians for data analysis and developing statistical software. Users have created packages to augment the functions of the R language.

Popularity of R

R and its libraries implement various statistical techniques, including linear and nonlinear modeling, classical statistical tests, spatial and time-series analysis, classification, clustering, and others. For computationally intensive tasks, C, C++, and Fortran code can be linked and called at run time. Another of R's strengths is static graphics; it can produce publication-quality graphs that include mathematical symbols. According to user surveys and studies of scholarly literature databases, R is one of the most commonly used programming languages used in data mining. As of March 2022, R ranks 11th in the TIOBE index, a measure of programming language popularity. R easily has more than two million active users around the world who all contribute to it's ongoing development.

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R Starting Points

rMarkdown Files

R Markdown documents are fully reproducible. Use a productive notebook interface to weave together narrative text and code to produce elegantly formatted output. Use multiple languages including R, Python, and SQL.

R Markdown supports dozens of static and dynamic output formats including HTML, PDF, MS Word, Beamer, HTML5 slides, Tufte-style handouts, books, dashboards, shiny applications, scientific articles, websites, and more.

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