Predictive Analytics

Undergraduate | 2026

Course page banner
area/catalogue icon
Area/Catalogue
STAT X400
Course ID icon
Course ID
208193
Level of study
Level of study
Undergraduate
Unit value icon
Unit value
6
Course level icon
Course level
4
Study abroad and student exchange icon
Inbound study abroad and exchange
Inbound study abroad and exchange
The fee you pay will depend on the number and type of courses you study.
Yes
University-wide elective icon
University-wide elective course
Yes
Single course enrollment
Single course enrolment
Yes
alt
Note:
Course data is interim and subject to change

Course overview

Predicting the unobserved has become an increasingly popular tool in statistics. It can provide a unifying framework to achieve many goals in statistical analysis - imputing missing data, predicting the future, predicting unobserved members of the population and what the impact of a particular treatment would be if it was administered. In this course students will build upon a core understanding of these specialist statistical areas to unify them with a central theory. In doing so, students will embed cutting edge research in assessing the quality of prediction and contemplate current challenges in the field.

Course learning outcomes

  • Distil common statistical tasks into a predictive task using Ruben’s potential outcomes framework
  • Analyse data with structure for a specific prediction task using Bayesian inference or machine learning
  • Propose validation and scoring schemes for different structures of data and prediction tasks
  • Interpret original research articles in the context of an applied problem
  • Translate approximate cross-validation algorithms into code
  • Present predictions to different audiences with a particular focus on limitations and assumptions

Prerequisite(s)

N/A

Corequisite(s)

N/A

Antirequisite(s)

N/A