Students will learn to model and manage uncertainty and risk. Some of the most commonly used probability distributions will be introduced together with Monte Carlo simulations. The concept of Maximum Likelihood Estimation (MLE) will also be introduced, allowing the estimation of distribution parameters. Probabilistic methods and models will then be illustrated using appropriate examples and software.


Teaching Periods
Start and end dates
Last self-enrolment date
Census date
Last withdraw without fail date
Results released date

Learning outcomes

Students who successfully complete this unit will be able to:

  • Identify appropriate probability distributions for modelling chance occurrences
  • Simulate such distributions and obtain estimates of distribution parameters using the method of moments and maximum likelihood estimation
  • Navigate probabilistic methods for working with uncertainty
  • Formulate probabilistic models for risk in real world contexts
  • Use probabilistic models to design statistical systems for the management of risk and uncertainty

Teaching methods

Hawthorn Online

Type Hours per week Number of weeks Total (number of hours)
Directed Online Learning and Independent Learning
12.50 12 weeks 150


Type Hours per week Number of weeks Total (number of hours)
Face to Face Contact (Phasing out)
3.00 12 weeks 36
Specified Learning Activities (Phasing out)
2.00 12 weeks 24
Unspecified Learning Activities (Phasing out)
Independent Learning
7.50 12 weeks 90


Type Task Weighting ULO's
Assignment 2Individual 40% 2,3,4 
ExaminationIndividual 50% 1,4,5 
Online QuizzesIndividual 10% 1,5 


  • Introduction to commonly used probability distributions
  • Introduction to Method of Moments and Maximum Likelihood Estimation (MLE) for estimation purposes
  • Applications for discrete, continuous and mixture distributions
  • Applications for univariate and multivariate distributions
  • Development of statistical models for identifying risk factors
  • Formulation of commonly used probabilistic models and systems for managing uncertainty (e.g. Acceptance Sampling, Process Control, Queuing Theory, Inventory Control, Reliability Theory, Markov Processes)

Study resources

Reading materials

A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.