Libraries offer workshops on data management, research reproducibility in R

UNIVERSITY PARK, Pennsylvania – Beginning September 19, Penn State University Libraries’ Department of Research Computing and Publishing will offer a series of four online workshops on data management and research reproducibility in A. The purpose of these sessions is to introduce resources and expertise available in university libraries.

R is a statistical programming language that allows users to manage data sets, manage analysis workflows, conduct statistical analysis, and create data visualizations. This series of workshops will provide hands-on training in fundamental coding skills, data visualization, and data management strategies in R to support research reproducibility. Attendees can expect to learn how to package 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.

Workshops are free and open to Penn State graduate students, postdoctoral researchers, faculty, and staff. No prior knowledge of R is required.

Since the workshops build on each other, participants must complete them in order. The first workshop, “The Basics of R and RStudio”, is optional but 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 the R, RStudio and Git applications. Registrants will receive instructions on how to access these applications prior to the start of the workshops.

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

Registration is required before September 12. Click here to subscribe to the series.

For more information, contact Research Informatics and Publishing at [email protected]

Workshop schedule

Basics of R and RStudio

Sept. 19, 2 p.m. to 4 p.m.

Data processing in R

Sept. 22, 2 p.m. to 4 p.m.

Data management and research reproducibility in RStudio

Sept. 29, 2 p.m. to 4 p.m.

Data Visualization in R

Oct. 6, 2 p.m. to 4 p.m.

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