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STAT378: Statistical Computing
This unit develops basic computer-intensive statistical methods. Many of them find applications in scientific research and industry. Topics include: Monte-Carlo simulation; bootstrapping; regression computations which include collinearity diagnostic and models selection using cross-validation; alternatives to least squares; ridge regression, weighted least squares and logistic regression; maximum likelihood computations using iterative methods, such as Newton-Raphson and Fisher scoring, and applications of the maximum likelihood method.
| Credit Points: | 3 |
| Contact Hours: | 4 |
| When Offered: | D1 - Day; Offered in the first half-year |
| Staff Contact(s): | Dr Jun Ma |
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| Corequisites: | |
| NCCW(s): | |
| Unit Designation(s): | |
| Assessed As: | Graded |
| Offered By: | Department of Statistics |
Timetable Information
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