STA 891
Topics for Preliminary Exam Preparation in Statistical Science
Filippo Ascolani, Mine Cetinkaya-Rundel, Merlise A. Clyde, David B. Dunson, Amy H. Herring, Peter D. Hoff, Edwin S. Iversen, Yue Jiang, Anya Katsevich, Eric Benjamin Laber, Fan Li, Sifan Liu, Simon tsz fung Mak, Omar Melikechi, Galen Reeves, Jerry P. Reiter, Colin Witter Rundel, Scott C. Schmidler, Rebecca Steorts, Dawn Strickland, Maria A. Tackett, Surya Tapas Tokdar, Alexander Volfovsky, Lasse Vuursteen, John Cameron Zito
Description from DukeHub
Directed readings in preparation for the PhD preliminary exam. Prerequisite: Core courses Statistical Science 702, 711, 721, 723, 732, and 831.
Skills
- data and statisticstitle: "statistical"
AI-resilient: 0 of 5
- No: Physical, lab or field work
- No: Live work with people
- 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
More in STA
- Data Analysis and Statistical Inference STA 101L
- Studying Incarceration with Data STA 116CNL
- Introduction to Data Science and Statistical Thinking STA 199CCL
- Regression Analysis STA 210L
- Regression Analysis: Theory and Applications STA 221L
- Statistical Computing STA 323L