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This course covers the statistical principles, data analysis techniques, the software analysis methods, and implementation in R, for Generalised Linear Models (GLM) and Multivariate Models.
STAT446 is a course in generalised linear models (GLM), a very useful and frequently used class of models for practical data analysis. Additional to normally distributed responses, a GLM allows us to model count data (0, 1, 2, 3, ...), binary data (success/failure, alive/dead, pass/fail, etc.), or categorical data (A/B/C/D, never/sometimes/often, etc.).Topics that are usually covered in the course include:• Exponential families• Link functions• Binary regression models• Modelling count data• Iteratively re-weighted least-squares• Likelihood inference / profile likelihood• Modelling overdispersion• Extensions to generalised linear mixed-effects models (GLMM)• Time-to-event modelling
Understand the concept of generalised linear modelsApply generalised linear (mixed-effects) models to count and categorical data Adequately report and interpret model results
This course will provide students with an opportunity to develop the Graduate Attributes specified below:
Critically competent in a core academic discipline of their award
Students know and can critically evaluate and, where applicable, apply this knowledge to topics/issues within their majoring subject.
Employable, innovative and enterprising
Students will develop key skills and attributes sought by employers that can be used in a range of applications.
Subject to approval of the Head of School.
Students must attend one activity from each section.
Daniel Gerhard
Note: To pass this course, you must both pass the course as a whole (≥50% over all the assessment items) and obtain at least 40% in the final examination.
Course requirementsYou should be familiar with• the fundamentals of probabilistic modelling: ◦ probabilities ◦ distribution functions ◦ densities ◦ expected values ◦ likelihood functions ◦ estimators ◦ the central limit theorem• Linear regression• basic knowledge of using the statistical software R
Domestic fee $1,138.00
International Postgraduate fees
* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.
For further information see Mathematics and Statistics .