STATS 330 Advanced Statistical Modelling

Below description edited in year: 2018

Points: 15

Prereqs: 15 points from STATS 201, 207, 208 or B+ in BIOSCI 209

Credit: Final exam 60%; coursework 40% (1 test worth 20% and assignments worth 20%), must obtain at least 50% in final exam to pass.

Textbooks: Course notes available from the Student Resource Centre.

Website: STATS 330 website

The main emphasis of STATS 330 is on analysing data using extensions of the regression methods seen in STATS 201/8. These extensions permit, for example, the building of models for response variables which are not continuous. The main statistical computer package used is R. Students from STATS 210 who have not taken STATS 201/8 will need to do some preparatory reading. STATS 330 is very useful for almost all subjects in Business and Economics, for Operations Research, for any experimental or social science. It is also a useful complement to Computer Science.

Topics studied include: Application of the generalised linear model to fit data arising from a wide range of sources, including multiple linear regression models, log-linear models and logistic regression models. The graphical exploration of data. Time allowing, we may also cover generalized additive models, including smoothing (e.g., regression splines) as well as negative binomial regression.

The course is based on R and has a significant practical component.

Disclaimer:
Although every reasonable effort is made to ensure accuracy, this information for the course year (2025) is provided as a general guide only for students and is subject to alteration. All students enrolling at the University of Auckland must consult its official document, the University of Auckland Calendar, to ensure that they are aware of and comply with all regulations, requirements and policies.