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Reproducibility: Data Management, Git, and RStudio

In response to a growing focus on the importance of reproducibility, replication, and transparency in the research endeavor, scholars are adapting their practices and learning new skills and tools. This workshop will introduce some general data management strategies that can increase the reproducibility of your work. You will also learn through hands-on exercises how to harness two specific tools, git and RStudio, to support the execution of more reproducible research projects. Git is a powerful version control system and RStudio is an open-source statistical software program. 

To fully participate in this workshop, please bring your own laptop.  The Hands-on part of this workshop focuses on the practical aspects of configuring RStudio with Git.  If you don't intend to use the R programming language, you may want to take a different workshop.

Prerequisite:  Intro to R. All attendees are expected to be basically familiar with R, R Studio.  For your convenience you can watch a previous recording of Intro to R and work through the practice datasets on your own.

Monday, January 29, 2018
1:00pm - 3:00pm
Bostock 023 Training Room
West Campus
Data and Visualization  
Registration has closed.

Event Organizer

Profile photo of John Little
John Little
Profile photo of Sophia Lafferty-Hess
Sophia Lafferty-Hess
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Center for Data and Visualization Sciences