The Practice of Reproducible Research

Catalog description

The course will focus on computational approaches to ensure that all data, code, and analyses can be captured in a reproducible workflow, to be confirmed and replicated by you in the future, by other members of your team, and by reviewers and other researchers. We will cover how to satisfy FAIR principles, version control, how to create a git repository, utilize Github and how to create a reproducible dataset. Prerequisites: Basic knowledge of R. Recommended (not required): EPI 202 or 261/262, STATS 60, or MS&E 125.