Reproducible and Collaborative Statistical Data Science
A project-based introduction to statistical data analysis. Through case studies, computer laboratories, and a term project, students learn practical techniques and tools for producing statistically sound and appropriate, reproducible, and verifiable computational answers to scientific questions. Course emphasizes version control, testing, process automation, code review, and collaborative programming. Software tools include Bash, Git, Python, and LaTeX.
- Jarrod Millman
- OH: Th 11A-12P in 210Q BARKER
- Ross Barnowski
- OH: W 2-4P in 444 EVANS
- Session Dates: 08/27-12/11/15
- Class meets TuTh 930-11A in 150 GSPP
- Lab meets M 10-12P or 12-2P in 340 EVANS
- CCN: 87680 (Stat 159) and 87812 (Stat 259)
Prerequisites: Stat 133, Stat 134, and Stat 135 (or equivalent). Graduate standing is required to register for Stat 259.