
R: What is R? - The R Project for Statistical Computing
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 …
The R Project for Statistical Computing
Jun 13, 2025 · If you have questions about R like how to download and install the software, or what the license terms are, please read our answers to frequently asked questions before you …
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An Introduction to R
There are now a number of books which describe how to use R for data analysis and statistics, and documentation for S/S-Plus can typically be used with R, keeping the differences between …
As a side-effect, the R system for statistical computing is available to everyone. All scientists, especially includ-ing those working in developing countries, have access to state-of-the-art …
These notes are designed to allow individuals who have a basic grounding in statistical methodology to work through examples that demonstrate the use of R for a range of types of …
The Comprehensive R Archive Network
The Comprehensive R Archive Network (CRAN) provides access to resources, packages, and documentation for the R programming language.
CRAN Task View: Sports Analytics
Sep 9, 2025 · NBAloveR is an R interface to access basketball data from Basketball Reference API. This package also contains functions to help users with analyzing basketball data.
R-4.5.1 for Windows - The Comprehensive R Archive Network
Please see the R FAQ for general information about R and the R Windows FAQ for Windows-specific information.
Exploratory Data Analysis - The Comprehensive R Archive Network
Aug 31, 2025 · This document introduces EDA (Exploratory Data Analysis) methods provided by the dlookr package. You will learn how to EDA of tbl_df data that inherits from data.frame and …
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R Data Import/Export
Since all data being manipulated by R are resident in memory, and several copies of the data can be created during execution of a function, R is not well suited to extremely large data sets.