Learning R: The Statistical Programming Language

The R program is becoming increasingly popular as a tool for data science and data analytics. It is an Open Source project and its power and flexibility have made it the goto choice in business, academia and government.

These resource pages are intended to help you learn R.

R is an open-source (GPL) statistical environment modelled after S and S-Plus. The S language was developed in the late 1980s at AT&T labs. The R project was started by Robert Gentleman and Ross Ihaka (hence the name, R) of the Statistics Department of the University of Auckland in 1995. It has quickly gained a widespread audience. It is currently maintained by the R core-development team, a hard-working, international team of volunteer developers. The R project web page is the main site for information on R. At this site are directions for obtaining the software, accompanying packages and other sources of documentation.

R is a powerful statistical program but it is first and foremost a programming language. Many routines have been written for R by people all over the world and made freely available from the R project website as “packages”. However, the basic installation (for Linux, Windows or Mac) contains a powerful set of tools for most purposes.

Because R is a programming language it can seem a bit daunting; you have to type in commands to get it to work. However, it does have a Graphical User Interface (GUI) to make things easier. You can also copy and paste text from other applications into it (e.g. word processors, but beware of “smart quotes”). So, if you have a library of these commands it is easy to pop in the ones you need for the task at hand.