While many researchers rely on SPSS or SAS to handle their statistical data, many users are starting to migrate to R software. Unlike SPSS and SAS, which are propriety and costly to buy, R is a free, open source software that may be used for computing statistics while conducting research. Besides the cost, there are many advantages to R. It works with Windows, Macintosh, UNIX, and Linux platforms. It runs wide variety of functions, from basic to advanced; functions such as data manipulation, graphics, and statistical modeling are available. Because the software is open sourced, many developers have written and distributed add-on packages at no cost to the user, in order to improve functionality.
While there are many advantages to R software, it is not without its downsides. Traditional software packages, like SPSS and SAS, have a very comprehensive user interface and are easy to use. For example, SPSS interface looks very much like an excel spreadsheet, with which most people are familiar and using. In contrast, R has a large learning curve and can be less user friendly. It relies more on programming and coding knowledge, with which many researchers do not have experience. However, there are sources online to help researchers learn the programming fundamentals that are required to use R. Another area where R lacks is in technical support. Both SPSS and SAS are commercial products and have customer/technical support available to users. Since R is open sourced software, there is no official support. However, a large community of R users can help one another troubleshoot problems and offer peer support to one another. If users are not comfortable with peer support, there are third party groups that provide support for R and respond to problems rather quickly.
R software can be downloaded and installed at https://cran.r-project.org
A session about R will be offered at the SHS Faculty Research Retreat on February 12, 1:30-2:30 PM.
This post was contributed by Annette Carr, Chief Librarian, Bay Shore and was originally published in ‘Significant Results: The Research Newsletter of the School of Health Sciences’ Volume 1, Issue 1. It is reprinted here with permission.