STA 101L
Data Analysis and Statistical Inference
John Cameron Zito
Description from DukeHub
Introduction to statistics as a science of understanding and analyzing data. Themes include data collection, exploratory analysis, inference, and modeling. Focus on principles underlying quantitative research in social sciences, humanities, and public policy. Research projects teach the process of scientific discovery and synthesis and critical evaluation of research and statistical arguments. Readings give perspective on why in 1950, S. Wilks said, 'Statistical thinking will one day be as necessary a qualification for efficient citizenship as the ability to read and write.' See department website for placement information. Not open to students who have taken Statistical Science 100 or above.
Skills
- data and statisticsdescription: "statistics" and 6 more
- lab workhas a lab component
- research methodsAI review: "Research projects teach the process of scientific discovery"
AI-resilient: 2 of 5
- Yes: Physical, lab or field work · "laboratory"
- No: Live work with people
- Yes: Judgment someone is accountable for · "policy"
- 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
- 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
- Statistical Methods for Sports Analytics STA 345