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.

No offerings have been identified for this subject in 2020.

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

HD/FL

Duration

One session

School

School of Computing and Mathematics

Assumed Knowledge

STA201 or STA401 or STA501

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; and
  • be able to produce a report that interprets the output for an academic or professional audience.

Syllabus

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

The information contained in the CSU Handbook was accurate at the date of publication: January 2020. The University reserves the right to vary the information at any time without notice.

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