Stat 159: Reproducible and Collaborative Statistical Data Science
UC Berkeley
Offerings
Overview
A project-based introduction to statistical data analysis. Through case studies, computer laboratories, and a term project, students will 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 may include Bash, Git, Python, and LaTeX.
Logistics
Three hours of lecture and two hours of laboratory per week.
Prerequisites
Statistics 133, Statistics 134, and Statistics 135 (or equivalent).