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3975 (v.4) Applied Statistics 302
Area: Department of Mathematics and Statistics Contact Hours: 4.0 Credits: 25.0 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
The analysis and interpretation of research data arising from more complex designs. Review of matrix algebra-random vectors, mean vectors and covariance matrices. Multivariate normal distribution. Generalised linear models. Maximum likelihood estimation and inferences for GLMs. Introduction to multivariate statistical methods using R and SAS. Methods for categorical data.
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