This is a 10-week lecture-based course focused on introducing the very foundation of probability, the celebrated measure theory, which ends a hundreds-of-years debate of Bayesian v.s. Frequentist. This course covers measure spaces, measurable functions over measure spaces, Lebesgue integration of measurable functions, product spaces and measure-theoretical Fubini's theorem, measure-theoretical random variables, and lastly, modes of convergence and their implications in probability theory (particularly, law of large numbers and central limit theorem).
STAT559: Measure Theory (2021)
Check the Syllabus for detailed course plan.
Instructor: Fang Han (firstname.lastname@example.org)
Grader: Zhenman Yuan (email@example.com)
Lectures: WF 11:30-12:50, on Zoom
Office hour: M 9-10, on Zoom
Midterm: 05/07, in-class
Final: 06/04, in-class