Academics

Libraries to offer workshops on data management, research reproducibility in R

Credit: University Libraries / Penn StateCreative Commons

UNIVERSITY PARK, Pa. — Beginning Sept. 19, the Research Informatics and Publishing department at Penn State University Libraries will offer a series of four online workshops on data management and research reproducibility in R. The goal of these sessions is to introduce resources and expertise that are available through the University Libraries.

R is a statistical programming language that allows users to wrangle data sets, manage analysis workflows, conduct statistical analyses, and create data visualizations. This workshop series will offer hands-on training in fundamental coding skills, data visualization, and data management strategies in R to support research reproducibility. Participants can expect to learn how to wrangle data into an analysis-ready format, use R packages and connections to manage R projects, and create data visualizations using an R package called ggplot2.

The workshops are free and open to Penn State graduate students, postdoctoral scholars, faculty and staff. No previous knowledge of R is required.  

Because the workshops build upon one another, participants are expected to complete each one in sequence. The first workshop, “Basics of R and RStudio,” is optional but is recommended for those who have never used R or RStudio before. 

Participants must have access to a computer with a Mac, Linux or Windows operating system and be able to download R, RStudio and Git applications. Registrants will receive instructions on how to access these applications before the workshops begin.

All workshops will be held via Zoom. Access information will be distributed via email prior to the start of the series.

Registration is required by Sept. 12. Click here to register for the series.

For additional information, contact Research Informatics and Publishing at repub@psu.edu.

Workshop Schedule

Basics of R and RStudio

Sept. 19, 2 to 4 p.m.

Data Wrangling in R

Sept. 22, 2 to 4 p.m.

Data Management and Research Reproducibility in RStudio

Sept. 29, 2 to 4 p.m.

Data Visualization in R

Oct. 6, 2 to 4 p.m.

Last Updated September 6, 2022

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