Statistical Computing - STAT378
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 |
| When Offered: | S2 Day - Session 2, North Ryde, Day |
| Staff Contact(s): | Associate Professor Jun Ma |
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| Assessed As: | Graded |
| Offered By: | Department of Statistics Faculty of Science and Engineering |
Course structures, including unit offerings, are subject to change.
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