• Total units 48 Units
  • Areas of interest Statistics
  • Major code APST-MAJ

As John Naisbett said of modern society, “we are drowning in information but starved for knowledge”. One of the most in-demand roles these days is that of applied statistician – the key person essential for decision-making and for understanding our data-driven world. In this major, you will learn to understand and use a wide array of statistical modelling techniques that will empower you to make sense of data and offer insights to a wide variety of disciplines, from archaeology to zoology and almost everything in between. If there are data, there is a need for applied statistics.

Learning Outcomes

  1. Exhibit a working knowledge of the statistical computing package R.


  3. Apply basic principles in the design of simple experiments.

  4. Communicate the role of generalized linear modelling techniques (GLMs) in modern applied statistics and implement GLM methodology.

  5. Effectively communicate statistical analyses graphically, numerically and in written reports

  6. Describe statistical models of transfer between multiple states, including processes with single or multiple decrements, and derive relationships between probabilities of transfer and transition intensities

  7. Interpret the results of a Bayesian analysis and perform Bayesian model evaluation and assessment.

  8. Formulate a Bayesian solution to real-data problems.

Other Information

Students will need to complete all of the following courses in order to be able to complete the 48 units of this major:

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30 units from completion of the following compulsory courses:

STAT3011 Graphical Data Analysis

STAT3012 Design of Experiments and Surveys

STAT3015 Generalised Linear Modelling

STAT3016 Introduction to Bayesian Data Analysis

STAT3032 Survival Models


6 units from completion of courses from the subject area EMET Econometrics


12 units from completion of further courses from the subject area STAT Statistics

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