You are viewing this page as an international student.
Change to Domestic

You are a domestic student if you are an Australian citizen, a New Zealand citizen or the holder of an Australian permanent visa.

You are an international student whether you are within or outside Australia and you do not meet the domestic student criteria.

COVID-19 (coronavirus): Latest advice for the Bond community.

DTSC13-307: Advanced Statistical Learning Models


This subject extends the investigation of modern statistical modelling techniques initiated in Statistical Learning and Regression Models. Topics include models for correlated data including spatial and mixed-effects models, as well as Bayesian hierarchical models including discussion of Markov chain Monte Carlo (MCMC) techniques for calculating posterior estimates, and modern applied re-sampling methods for developing robust measures of model accuracy.  The programming language R will be used in this subject.

Subject details

FacultyBond Business School
Semesters offered
  • May 2022 [Standard Offering]
  • September 2023 [Standard Offering]
Study areas
  • Business and Commerce
Subject fees
  • Commencing in 2022: $5,260
  • Commencing in 2023: $5,400

Learning outcomes

1. Demonstrate knowledge of the statistical issues associated with correlated data and random effects. 2. Evaluate and choose between a variety of advanced statistical model structures. 3. Diagnose key aspects of data structures to assess the need for correlational(?) or hierarchical structure. 4. Apply the Bayesian modelling framework, including the use of Markov chain Monte Carlo techniques to find posterior estimates. 5. Apply resampling methods to develop robust measures of model accuracy. 6. Explain the meaning and importance of the results of statistical models with random effects and hierarchical structure.

Enrolment requirements

Requisites: ?

Pre-requisites: ?

Co-requisites: ?

There are no co-requisites.

Restrictions: ?


Subject dates

Standard Offering
Enrolment opens20/03/2022
Semester start16/05/2022
Subject start16/05/2022
Cancellation 1?30/05/2022
Cancellation 2?06/06/2022
Last enrolment29/05/2022
Withdraw – Financial?11/06/2022
Withdraw – Academic?02/07/2022
Teaching census?10/06/2022