Area: | Department of Mathematics and Statistics |
Credits: | 25.0 |
Contact Hours: | 4.0 |
Lecture: | 1 x 3 Hours Weekly |
Tutorial: | 1 x 1 Hours Weekly |
Prerequisite(s): | 301344 (v.2) Probability Concepts 570 or any previous version
AND
301349 (v.2) Mathematical Methods 560 or any previous version
AND
301350 (v.2) Statistical Methods 560 or any previous version
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Syllabus: | Review of matrix algebra - random vectors, mean vectors and covariance matrices, multivariate normal distributions, generalised linear models, maximum likelihood estimation and inference, introduction to multivariate statistical methods using MINITAB and SAS, multivariate analysis o variance, principal component analysis, distriminant analysis, factor analysis. |
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Unit Outcomes: | To develop practical skills in the applications of multivariate statistical techniques. To learn to use SAS statistical computing package. Though this unit is intended to be applied in nature, it should be realised that much of what will be covered hasto be supported by relevant theory. |
Field of Education: | 10100 Mathematical Sciences (Narrow Grouping) | HECS Band (if applicable): | 2 |
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Extent to which this unit or thesis utilises online information: | Not Online | Result Type: | Grade/Mark |
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Availability
| Year | Location | Period | Internal | Area External | Central External | | 2004 | Bentley Campus | Semester 2 | Y | | |
Area
External | refers to external course/units run by the School or Department, offered online or through Web CT, or offered by research. |
Central
External | refers to external course/units run through the Curtin Bentley-based Distance Education Area |
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