Introduction:
R is a programming language and an open source software that specializes in statisical computing and visualization. In the early 1990’s, two statistics professors, Ross Ihaka and Robert Gentleman, developed R at the University of Auckland in New Zealand [1]. Their goal was to build on prior data analysis software to make it more understandable and economically feasible for their statisics students. The R Foundation identifies R as an implementation of S; S is a computer language and environment that was developed by John Chambers and other researchers at Bell Laboratories in 1976 [2]. Much of R remains unaltered from its foundational language, S, but Ihaka and Gentleman also incorporated the semantics of Scheme, another programming language, to create R’s system.
Literature Review:
R’s widespread popularity is largely in part due to it being a free, open source program. The software truly represents a collaborative experience in which all users can modify, improve, or distribute its code. Users can create packages for R that further enhances its capabilities; packages may contain algorithums, complex maps, and graphs, and other statistical tools [3]. Packages are stored in CRAN, the Comprehensive R Archive Network, and supporting members can address and report issues with packages [4]. The Free Software Foundation and the GNU General Public License ensure that R remains a free, open source software.
The R system is designed as a command-driven interface, which means that users type in text/code and tell R to execute (“knit”) it. Many updated, modern softwares have menus or drop-down lists where users make selections on how they want a software to interact and analyze data [5]. R was not developed as a menu-based interface due to the limited flexibilities of these softwares. However, for users who desire the menu-based inferace, there is an R package titled Rcmdr which contains the R Commander. The R Commander is a graphical user interface that provides users with a list of available options to: load data in R, create visual models, manipulate data values, and perform various statistical analyses [6].This package highlights the benefits of R in which a user does not even have to necessarily understand or master the programming language to utilize it.
Some users may decide that they rather interact with R in an environment that is more readily straightforward and equipped with convenient statistical tools and features, this integrated development environment (IDE) is formally known as RStudio. RStudio contains a console panel in which users will run R code [7]. RStudio features specific tabs that enable users to quickly adapt to the R system by finding the tabs that relate to their current objectives, such as searching for packages or a tad on the far right that indicates importing data.
References
Fox, John & Leanage, Allison. 2016. “R and the Journal of Statistical Software.” Journal of Statistical Software. doi: 10.18637/jss.v073.i02.
“What is R? How do I use it?” Inter-university Consortium for Political and Social Research. https://www.icpsr.umich.edu/icpsrweb/content/shared/ICPSR/faqs/what-is-r.html.
“What is R?” The R Foundation. https://www.r-project.org/about.html
“R for Researchers: Introduction. Social Science Computing Comperative.” UW Board of Regents,University of Wisconsin - Madison. https://www.ssc.wisc.edu/sscc/pubs/RFR/RFR_Introduction.html.
Braun, W. John & Murdoch, Duncan J. 2016. “A First Course in Statistical Programming with R. Second Edition.” Cambridge University Press.
Fox, John. 2005. “The R Commander: A Basic-Statistics Graphical User Interface to R.” Journal of Statistical Software 14(9).
Ismay, Chester & Kim, Albert Y. “What are R and RStudio?” Modern Dive. https://camo.githubusercontent.com/d4de9c9ba0dffd5c1c554345360df01f7d22e1e2/68747470733a2f2f692e696d6775722e636f6d2f4e664c37546a522e706e673f31.