3975 (v.5) Applied Statistics 302
Note
Tutition Patterns
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.
Unit references, texts and outcomes
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.
| Area: | Department of Mathematics and Statistics |
|---|---|
| Credits: | 25.0 |
| Contact Hours: | 4.0 |
| Lecture: | 1 x 3 Hours Weekly |
| Laboratory: | 1 x 1 Hours Weekly |
| Prerequisite(s): |
8128 (v.6)
Linear Algebra 202
or any previous version
AND 8393 (v.9) Experimental Design and Analysis 202 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, generalised linear models (GLM) and inferences for GLMs, one sample and two sample test of hypotheses on the mean vector: comparison of several mean vectors - multivariate analysis of variance (MANOVA), discriminant analysis. Analysis of multivariate data using statistical software like R and SAS (Statistical Analysis System). |
| Field of Education: | 010103 Statistics |
| SOLT (Online) Definitions*: | Informational *Extent to which this unit or thesis utilises online information |
| Result Type: | Grade/Mark |
Availability
Availability Information has not been provided by the respective School or Area. Prospective students should contact the School or Area listed above for further information.
