STA 199: Intro to Data Science

Intro to data science and statistical thinking. Learn to explore, visualize, and analyze data to understand natural phenomena, investigate patterns, model outcomes, and make predictions, and do so in a reproducible and shareable manner. Gain experience in data wrangling and munging, exploratory data analysis, predictive modeling, and data visualization, and effective communication of results. Work on problems and case studies inspired by and based on real-world questions and data. The course will focus on the R statistical computing language.

Course info


  French 2231

  Mon and Wed 3:05 - 4:20


  Soc Sci 311

  Thur 1:25 - 2:40    or      Thur 3:05 - 4:20    or      Thur 4:40 - 5:55

Teaching team and office hours

Instructor Mine Çetinkaya-Rundel     Tue 11:00 - 12:30 and Thur 10:00 - 11:30 Old Chem 213
TAs Peter Hase   Sun 1:00 - 3:00 Old Chem 211A
Walker Harrison     Tue 10:00 - 11:00 and 1:30-2:30 Old Chem 211A
Gary Larson   Mon 12:00 - 2:00 Old Chem 211A
Sarah Sibley   Sat 12:00 - 2:00 Old Chem 211A


All texts are freely available online:

R for Data Science Grolemund, Wickham O'Reilly, 1st edition, 2016
OpenIntro Statistics Diez, Barr, Çetinkaya-Rundel CreateSpace, 3rd Edition, 2015
OpenIntro Data Science (link TBA) Çetinkaya-Rundel In progress


You should have access to a laptop and bring it to every class, fully charged.

Green Classroom

This course has achieved Duke’s Green Classroom Certification. The certification indicates that the faculty member teaching this course has taken significant steps to green the delivery of this course. Your faculty member has completed a checklist indicating their common practices in areas of this course that have an environmental impact, such as paper and energy consumption. Some common practices implemented by faculty to reduce the environmental impact of their course include allowing electronic submission of assignments, providing online readings and turning off lights and electronics in the classroom when they are not in use. The eco-friendly aspects of course delivery may vary by faculty, by course and throughout the semester. Learn more at