Statistical Foundations of Econometrics and Data Science

Description from DukeHub

Rigorous introduction to statistical concepts that underpin econometrics. Course emphasizes conceptual understanding, uses mathematics to illustrate ideas, and applies ideas to examples from economics broadly construed. Students analyze data to reinforce understanding. Topics include experimental and non-experimental research designs; modern approaches to summarizing data; random variables, probability, expectations, density and distribution functions; sampling; estimation; inference and hypothesis testing; introduction to linear regression. First course in two-semester econometrics sequence. Prerequisite: Mathematics 21, 106L,111L, 112L, 121, 122, 122L, 202, 202D, 212, or 222.

Skills

• data and statisticsdescription: "statistical" and 5 more

AI-resilient: 0 of 5 0/5

• 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

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