Graduate Course Descriptions

The following directory lists the graduate courses which the University expects to offer, although the University in no way guarantees that all such courses will be offered in any given academic year, and reserves the right to alter the list if conditions warrant. Click on the links below for a list of courses in that subject area. You may then click “View Classes” to see scheduled classes for individual courses.

6325. Advanced Probability

3.00 credits

Prerequisites: Open to Ph.D. students who have passed the Ph.D. Qualifying Exam in Statistics, others with permission.

Grading Basis: Graded

Fundamentals of measure and integration theory: fields, o-fields, and measures; extension of measures; Lebesgue-Stieltjes measures and distribution functions; measurable functions and integration theorems; the Radon-Nikodym Theorem, product measures, and Fubini's Theorem. Introduction to measure-theoretic probability: probability spaces and random variables; expectation and moments; independence, conditioning, the Borel-Cantelli Lemmas, and other topics as time allows.


Last Refreshed: 20-JUN-24 05.20.07.060883 AM
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Term Class Number Campus Instruction Mode Instructor Section Session Schedule Enrollment Location Credits Grading Basis Notes
Fall 2024 8771 Storrs In Person Pozdnyakov, Vladimir 001 Reg TuTh 12:30pm‑1:45pm
6/40 AUST 163 3.00 Graded