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R is a free software environment for statistical computing and graphics For information on how to ask questions, see, e.g., the r mailing list posting guide, and the document about how to create reproducible examples for r on stack overflow. It compiles and runs on a wide variety of unix platforms, windows and macos

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R was started by professors ross ihaka and robert gentleman as a programming language to teach introductory statistics at the university of auckland R is not just a programming language, but it is also an interactive ecosystem including a runtime, libraries, development environments, and extensions All these features help you think about problems as a data scientist, while supporting fluent interaction between your brain and the computer. This course is a set of tutorials sorted by category in which you will learn all the basics (and some more advanced content) to handle the r programming language.

In this tutorial, we’ll walk through the steps to install and set up r on different operating systems (windows, macos, linux) By the end, you’ll be ready to start coding in r and explore the powerful tools for analyzing data, machine learning, and visualization. R is ‘gnu s’, a freely available language and environment for statistical computing and graphics which provides a wide variety of statistical and graphical techniques Linear and nonlinear modelling, statistical tests, time series analysis, classification, clustering, etc.

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.