Multivariate Statistical Analysis M
Postgraduate
Postgraduate
MATH 5036
Postgraduate
No
100849
4.5
No
School of Information Technology and Mathematical Sciences
To give students an understanding of the theory and practice of modern multivariate statistical methods.
The linear model; the multivariate normal distribution; covariance matrices; Hotelling's T-squared; principal components; Flury test, discriminant analysis; factor analysis.
Johnson, Richard A. & Wichern Dean W. 2000, Applied Multivariate Statistical Analysis, 5th edition, Prentice Hall, New Jersey
Assumed knowledge for this course is a thorough knowledge of first-year linear algebra which can be accessed through the course MATH 1056 Linear Algebra. The statistical prerequisite is the knowledge on basic statistical methods which can be accessed through the course MATH 1036 Statistical Methods.
Nil
Component | Duration | ||
---|---|---|---|
INTERNAL, CITY WEST | |||
Lecture | 3 hours x 13 weeks | ||
Tutorial | 1 hours x 12 weeks |
Note: These components may or may not be scheduled in every study period. Please refer to the timetable for further details.
Assignment 1, Assignment 2, Final examination
EFTSL*: 0.125
Commonwealth Supported program (Band 2)
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* Equivalent Full Time Study Load. Please note: all EFTSL values are published and calculated at ten decimal places. Values are displayed to three decimal places for ease of interpretation.