|Short Description:||Statistical Models|
|Faculty or Section :||Faculty of Health, Engineering and Sciences|
|School or Department :||School of Sciences|
|Student contribution band :||Band 1|
|ASCED code :||010103 - Statistics|
|Grading basis :||Graded|
|Version produced :||5 March 2021|
Pre-requisite: STA3300 or approval of examiner or Students must have completed STA8170 and be enrolled in one of the following Programs: GCSC or GDSI or MSCN or MADS or MSCR or DPHD.
This course introduces and extends the student's knowledge of linear models. The mathematical development of these models will be considered, however the focus will be on practical applications. The statistical program R will be introduced and used throughout the course. The topics include developing multiple regression models, testing hypotheses for these models, selecting the 'best' model, diagnosing problems in model fit, shrinkage methods, developing generalised linear models, and a range of applications of generalised linear models including logistic, Poisson and log-linear models. Analysis of different statistical models are practised using the statistical software package through the R and RStudio.