| Call Number | 15642 |
|---|---|
| Day & Time Location |
TR 1:00pm-2:20pm To be announced |
| Points | 3 |
| Grading Mode | Standard |
| Approvals Required | None |
| Instructor | Caleb Miles |
| Type | LECTURE |
| Method of Instruction | In-Person |
| Course Description | This course offers a general introduction to essential materials in advanced statistical theory for doctoral students in biostatistics. The course is designed to prepare doctoral students in biostatistics for their written theory qualifying exam. Students in this course will learn theory of estimation, confidence sets and hypothesis testing. Specific topics include a quick review of measure-theoretic probability theory, concepts of sufficiency and completeness, unbiased estimation (UMVUE), least squares principle, likelihood estimation, a variety of estimators and their asymptotic properties, confidence sets, the Neyman-Pearson lemma and uniformly most powerful tests. If time permits, the likelihood ratio test, score test and Wald test, and sequential analysis will be covered. |
| Web Site | Vergil |
| Department | Biostatistics |
| Enrollment | 0 students (7 max) as of 10:06AM Sunday, June 2, 2024 |
| Subject | Biostatistics |
| Number | P9109 |
| Section | 001 |
| Division | School of Public Health |
| Open To | GSAS, Public Health |
| Campus | Health Science |
| Section key | 20243BIST9109P001 |