Area: |
Department of Mathematics and Statistics |
Credits: |
25.0 |
Contact Hours: |
4.0 |
| |
| ** The tuition pattern below provides details of the types of classes and their duration. This is to be used as a guide only. For more precise information please check your unit outline. ** |
| |
Lecture: |
3 x 1 Hours Weekly |
Practical: |
1 x 1 Hours Weekly |
Prerequisite(s): |
8128 (v.6) Linear Algebra 202 or any previous version
AND
8393 (v.8) Statistical Methods 201 or any previous version
AND
302315 (v.2) Mathematical Statistics 202 or any previous version
|
| |
Syllabus: |
Introduction to multivariate statistical analysis. Review of matrix algebra. Random vectors, mean vectors, covariance and correlation matrices. Multivariate normal distribution and its properties. Random samples from the multivariate normal and sampling distributions thereof. Inference for multivariate normal parameters, maximum likelihood estimation, GLM and inferences for GLMS, one sample and two sample test of hypotheses on the mean vector, comparison of several mean vectors - multivariate analysis ofvariance (MANOVA), discriminant analysis. Analysis of multivariate data using statistical software like R and SAS. |
| |
| ** To ensure that the most up-to-date information about unit references, texts and outcomes appears, they will be provided in your unit outline prior to commencement. ** |
| |
Field of Education: |
20300 Information Systems (Narrow Grouping) |
HECS Band (if applicable): |
2 |
|
Extent to which this unit or thesis
utilises online information: |
Informational |
Result Type: |
Grade/Mark |
|
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 |
|
