In the summer of 2020, the Wayne State University Research Design and Analysis Unit (RDA) launched a workshop that introduces students to R software. R is a common statistical programming language that helps users analyze and manage data. The RDA helps graduate students and postdoctoral scholars design research projects and conduct statistical analysis. The unit decided to launch the workshop after noticing a gap in the method and statistical training of the walk-ins requesting assistance. A gap students across campus obviously felt; the registration limit was capped within hours of the interest form going live. To meet the demand, the RDA decided to host these workshops semesterly. 

Bridging the talent gap

Advanced degree holders are increasingly targeting careers outside of academe. In the era of COVID-19, an already hyper-competitive academic job market has become even more volatile, plagued by hiring freezes, furloughs, and budget cuts. The pressure is on Ph.D. programs to prepare their students for alternative careers in private and public industry. Helping students learn open-source statistical software is a prime place to start.

Data science is one of the fastest growing fields in the U.S. Even those not working directly in data analytics, industry professionals are required to use and interpret data to a greater extent than ever before. It is not only the corporate, government, and STEM sectors; non-profit, philanthropy, and human service sectors are incorporating data analysis to an unprecedented level in their work. However, proprietary statistical software (e.g., SPSS, STATA, SAS) are often not available to industry professionals due to the associated cost. Even within academe, these software packages cannot keep pace with the rapid advances in analytic methods in bio-social sciences. They also present a substantial cost to universities which are facing persistent financial challenges. In contrast, R software is free to use and open-source.

For the RDA workshop, prior experience in R is not required. Graduate students, postdoctoral scholars and faculty from any discipline can participate. The format is a combination of online demonstrations, lectures, hands-on activities, and an independent final project. Participants can expect to learn the importing and exporting of data, R data structures, strategies for data manipulation, how to conduct basic statistical analyses, and how to graph the results. Although students do not receive formal credit on their transcript for participating in the workshop, they receive a certificate of participation upon completion.

Testimonials

What's it like to attend a R workshop with the RDA? Two graduate students who participated in the summer session offer their insight.

Katheryn Szechy, doctoral student in the School of Social Work
After returning to graduate school, I began to hear from other students and faculty about using R for its flexibility and capability for more advanced and specialized analysis. I made some attempts to learn R software on my own, but I struggled with understanding the environment and how to use the code. From the first session with the RDA, I could tell that I was going to advance way beyond what I might learn on my own.

Because it's an open-source software, I have control over obtaining, using and updating R. If I move on to another institution or industry, I don't have to be concerned about purchasing software or obtaining a software license. And there's a vibrant online community of R users full of advice, ideas and sharing of code. I can use that virtual community for ongoing support.

Silviya Gancheva, doctoral candidate in the Department of Political Science
Hands down this was a fantastic experience! You get the support you need, and the instructors are not only knowledgeable and explain R language, they are dedicated. They will help you find additional resources and answer all the questions you may have. You are given all the necessary skills, not only to complete an assignment, but to use this R code and your new skills in your own research. It is intense and requires time and energy, but so do all other things you want to be better at and improve. I found the workshop quite flexible, as I had the freedom to decide when to review the material and how to organize my week around the assignments.

Looking back, enrolling in this seminar has been the best decision I have made in 2020. If I could give advice to future graduate students, I'd say: Take Introduction to R as soon as you can - you will fall in love with it! Look at me now, six weeks ago I did not know what Bayesian statistics are, now I am running my own Bayesian logistic regression on my brand new COVID-19 data! You cannot get more 2020 than that!

In addition to the workshops, the RDA provides on-on-one consulting, available by appointment. Contact the RDA for more information at RDAUnit@wayne.edu.

For more information on available services, visit the RDA website.

Written by RDA consultants Laura Pineault and Sabrina Bierstetel, and RDA Unit Director Robert Partridge, Ph.D.