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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

6cp at 200 level including (STAT272 or STAT273 or STAT278Prerequisite Information


Unit Designation(s):



Unit Type:
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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