STA 323L
Statistical Computing
Colin Witter Rundel
Description from DukeHub
A practical introduction to statistical programming focusing on the R programming language. Students will engage with the programming challenges inherent in the various stages of modern statistical analyses, including everything from data collection/aggregation/cleaning to visualization and exploratory analysis to statistical model building and evaluation. This course places an emphasis on modern approaches/best practices for programming, including source control, collaborative coding, literate and reproducible programming, and distributed and multicore computing. Prerequisite: STA 198CNL, 198L, 199CCL, 199L, or an STA course 200-level and above.
Skills
- programmingdescription: "programming" and 5 more
- data and statisticsdescription: "statistical" and 3 more
- lab workhas a lab component
AI-resilient: 2 of 5
- Yes: Physical, lab or field work · "laboratory"
- Yes: Live work with people · "collaborative"
- No: Judgment someone is accountable for
- No: A craft you practice with your hands or body
- No: Small, in-person format
The checks lean on Microsoft Research, Working with AI (2025), which found generative AI applies least to physical work and hands-on work with people. A signal, not a promise. How the score works
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