Units / ETF2020
ETF2020 · Statistical foundations of business analytics
2026 Handbook6 credit pointsLevel 2Department of Econometrics and Business Statistics
Last checked: 23 Aug 2026 UTCOverview
The business world is characterised by decision making in an environment of risk. To gain a deeper understanding of the tools and models used in business analytics, a strong foundation in probability and statistics is required. Probability provides a "language" for thinking about risk, while statistics provides a framework for making data-driven inferences and predictions. This unit provides a strong grounding in these fundamentals. Some of the topics covered may include risk v uncertainty v probability, famous statistical paradoxes, decision theory, frameworks for statistical inference (frequentist, Bayesian, etc.) and simulation and re-sampling. Examples from real world business problems will be used to motivate each topic.
Offerings
| Campus | Teaching period | Mode |
|---|---|---|
| Caulfield | Second semester | Activities scheduled as a mix of on-campus and online activities (BLENDED) |
| Caulfield | First semester | Activities scheduled as a mix of on-campus and online activities (BLENDED) |
Assessment
The Handbook lists an examination for this unit.
| # | Assessment | Type | Weight | Hurdle |
|---|---|---|---|---|
| 1 | 1 - Written | Written | 40% | — |
| 2 | 2 - Examination | Examination | 60% | — |
Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.
Requisites
prerequisite
- ETB1100 — Business statistics
- ETC1000 — Business and economic statistics
- ETF1100 — Business statistics
- ETW1001 — Introduction to statistical analysis
- FIT1006 — Business information analysis
- SCI1020 — Introduction to statistical reasoning
- STA1010 — Statistical methods for science
- ETX1100 — Business statistics
Joined by OR.
prohibitions
- ETC2520 — Probability and statistical inference for economics and business
Learning outcomes
- think and communicate about risk in a probabilistic way and apply this thinking to a business problem
- understand random variables, statistical distributions and conditional probability
- appreciate how conditional probabilities can be misinterpreted in business settings and how this is overcome with Bayes’ Rule
- frame a business problem using probability and statistics and make data-driven decision in the presence of risk
- apply the main methods of statistical estimation, prediction and inference and evaluate their properties
- evaluate and choose between different statistical models.
Workload
Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled learning activities and independent study. Independent study may include associated readings, assessment and preparation for scheduled activities. You are expected to complete all pre-class activities prior to your scheduled class, and post-class activities should be completed after your scheduled class. Learning activities may include a combination of teacher directed, peer directed and online engagement activities.
| Activity | Duration |
|---|---|
| Workshops | 12 hours |
| Tutorials | 12 hours |
| Seminars | 24 hours |
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