Session: Cutting Edge Analytical Tools: Why Should I Use R and How Do I Get Started? (Society for Social Work and Research 21st Annual Conference - Ensure Healthy Development for all Youth)

R, the free, open-source statistical programming language, is increasingly seen as “cutting edge.”  It has been estimated that contributions to R repositories have created more functionality in 2015 alone than in the entire history of SAS (Muenchen, 2015).  The capabilities of R are nearly limitless.  Despite this, the field of social work research has lagged behind other analytical fields in the use of R (B. Perron & Victor, 2016).

R has a reputation of having a steep learning curve with new users finding help files difficult to understand.  Other concerns that new users have is that R has too many commands, has multiple methods for conducting the same analysis, and has sparse output (Muenchen, 2014).

Despite the challenges that new users face when learning R, there are many advantages to learning how to use it.  For instance, R promotes reproducible research, encourages deep statistical thinking and produces outstanding graphics (B. E. Perron et al., 2016; Pruim, n.d.).  Additionally, user-built graphical user interfaces such as R-Commander and RStudio, have made it easier to use R by enabling users to easily store their histories, create scripts, export documents, manage datasets and update user-contributed packages.  In short, it is worthwhile to learn R.

Three papers will be presented in this symposium to help attendees reduce the learning curve associated with R.  The first paper, titled “Why Should I Use R? Top 10 Reasons for Learning Something New” will help demystify R by emphasizing its advantages and making the case for why an investment of time in learning new statistical software is worthwhile.  The remaining two papers are intended to help novice users get started with the nuts and bolts needed for further statistical analysis. “R Data Management” will teach attendees how to easily import data into R, recode variables, combine datasets, and create new variables.  “Introductory Statistics and Basic Graphs using R” will walk users through the basics of univariate and multivariate analysis and will also provide an overview of R’s robust visualization packages including “lattice” and “ggplot2.”

The presenters will make available to attendees all of the datasets and scripts used during the symposium so that they can get started with R on their own once the conference as concluded.