R is a computer programming language that is used for statistical computing and graphics (1). R is used for various statistical and graphical techniques (1). R is a free, open source program meaning anyone can modify, inspect, enhance, and share it because its design is publicly accessible (2). R was able to find a large following because statisticians, engineers, and scientists with no background in computer programming find it easy to use (3).
R was created by Ross Ihaka and Robert Gentleman in 1995 at the University of Auckland. The development of R was influenced by the languages S and Scheme (1). S was created by John Chambers in 1976 at Bell Labs. R is considered a different implementation of S (1). A lot of code written for S runs unchanged in R, although there are some important differences between the languages (1). R was created when Ihaka used S and thought there could be helpful additions made to S (6). They continued and created R with a similar syntax as S.
Originally the creators were wary about R being a free software but were persuaded by Martin Mächler. The R source code was released as free software by 1995 (6). The open source nature of R has helped it grow tremendously. In the beginning, R users didn’t have anywhere to share information with each other, so the creators had a small mailing list. As R’s popularity increased, mostly by word of mouth, the mailing list became impractical (6). This led to the creation of r-testers, then a year later it was replaced with r-announce, r-help, and r-devel. As the development of R continued the creators decided to create a better mailing list. This arose in part because of the number of reports and suggestions they were receiving to alter the code (6). It was difficult for the creators to keep up the extensive amount of contributions which is why the open source nature of the program is so effective.
R can be extended through the use of packages (1). Packages are collections of data sets and functions that have been created by the R community (4). They are used to increase the functionality of R by improving the existing base functions or by adding new ones (4). CRAN (Comprehensive R Archive Network) currently has 13,656 packages available (5). These packages are used for a wide range of things including adding advanced algorithms, colored and textured graphs (3) or natural language processing of Korean texts (4).