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| title | Stat 159: Reproducible and Collaborative Statistical Data Science | ||||
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{: .mb-2 } UC Berkeley {: .mb-0 .fs-6 .text-grey-dk-000 }
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.
Three hours of lecture and two hours of laboratory per week.
Statistics 133, Statistics 134, and Statistics 135 (or equivalent).