Introduction to Data-Analysis with R and Reproducible Data Science

Bruninks Hall Room 114


With the increasing availability of data with broad applications (and the sheer size of some of these data), it is more important than ever to be able to elucidate trends, decisions, and stories from data. This workshop will offer a hands on introduction to Data Science and Statistics using the free and publicly available software R. Assuming no background knowledge of software or Statistics, we will bring you up to speed on some foundational, modern, and popular data analysis techniques.

This short course is divided into multiple modules.  On day one we will explore the basic features of R and the power of R for constructing visualizations, summaries, tests, and regression models from data.  The modules on day two will include a gentle introduction to classification techniques (eg: trees) and conclude with an in-depth discussion on best practices for reproducible Data Science research and practice using R Markdown and github.


  • Students - $75
  • Faculty/Staff - $100
  • Other - $150

Register Here

A light breakfast and coffee will be served both days and attendees are on their own for lunch.


View the schedule


If you are attending from out of town, consider booking accommodation at the graduate hotel. It is a short walk to the short course site.

Additional Materials

Attendees should complete the participant checklist before attending the short course. If you have any difficulty doing this please email [email protected].

View participant checklist

View outline and resources for course participants


updated poster