STA427 Advanced Statistical Modelling (8)

This subject provides specialised knowledge in order to perform advanced statistical modelling through a range of generalised regression analyses and spatial analyses. The subject will focus on generalised linear models based on the exponential family of distributions, including the Binomial, Poisson and logistic regression, and highlight some basic techniques for spatial data analysis. A feature of this subject will be the analysis of practical problems with real life data using modern computer packages, and interpretation of results for a variety of audiences.


Session 2 (60)
Wagga Wagga Campus

Continuing students should consult the SAL for current offering details: STA427. Where differences exist between the Handbook and the SAL, the SAL should be taken as containing the correct subject offering details.

Subject Information

Grading System



One session


School of Computing and Mathematics

Assumed Knowledge

STA201 or STA401

Learning Outcomes

Upon successful completion of this subject, students should:
  • be able to explain the role of Generalised Linear Models (GLMs) and their applications;
  • be able to evaluate a given situation to select the appropriate generalised linear method by checking assumptions;
  • be able to perform statistical analyses associated with generalised linear models including the Binomial, Poisson and Logistic Regression models;
  • be able to sample spatial features, test their patterns, and estimate their densities using appropriate statistical techniques in spatial data analysis for a range of applications;
  • be able to produce a report that interprets the output for an academic or professional audience.


This subject will cover the following topics:
  • Exponential family of distributions.
  • R computer package.
  • Binary data.
  • Log-Linear models.
  • Gamma data.
  • Basic techniques for spatial data analysis


For further information about courses and subjects outlined in the CSU handbook please contact:

Current students

Future students

The information contained in the CSU Handbook was accurate at the date of publication: May 2019. The University reserves the right to vary the information at any time without notice.