| Call Number | 13417 |
|---|---|
| Day & Time Location |
MW 2:40pm-3:55pm 903 School of Social Work |
| Points | 4 |
| Grading Mode | Standard |
| Approvals Required | None |
| Instructor | Sumit Mukherjee |
| Type | LECTURE |
| Method of Instruction | In-Person |
| Course Description | Prerequisites: A thorough knowledge of elementary real analysis and some previous knowledge of probability. Overview of measure and integration theory. Probability spaces and measures, random variables and distribution functions. Independence, Borel-Cantelli lemma, zero-one laws. Expectation, uniform integrability, sums of independent random variables, stopping times, Wald's equations, elementary renewal theorems. Laws of large numbers. Characteristic functions. Central limit problem; Lindeberg-Feller theorem, infinitely divisible and stable distributions. Cramer's theorem, introduction to large deviations. Law of the iterated logarithm, Brownian motion, heat equation. |
| Web Site | Vergil |
| Department | Statistics |
| Enrollment | 17 students (25 max) as of 7:06PM Wednesday, May 1, 2024 |
| Subject | Statistics |
| Number | GR6301 |
| Section | 001 |
| Division | Graduate School of Arts and Sciences |
| Open To | GSAS |
| Campus | Morningside |
| Note | STAT PhD students only. |
| Section key | 20233STAT6301G001 |