Units / ETF3231
ETF3231 · Business forecasting
2026 Handbook6 credit pointsLevel 3Department of Econometrics and Business Statistics
Last checked: 23 Aug 2026 UTCOverview
Forecasts are crucial for guiding the planning and decision making process in business. In this unit you will learn to apply reliable methods for generating accurate forecasts in a rapidly changing business environment. These include: an introduction to regression modelling from a forecasting perspective, classical decomposition, exponential smoothing, Box-Jenkins ARIMA modelling and judgemental forecasting. You will build your programming skills by learning to program in R, a free programming language for statistical computing.
Offerings
| Campus | Teaching period | Mode |
|---|---|---|
| Caulfield | First semester | Teaching activities are on-campus (ON-CAMPUS) |
Assessment
The Handbook lists an examination for this unit.
| # | Assessment | Type | Weight | Hurdle |
|---|---|---|---|---|
| 1 | 1 - Quiz / Test | Quiz / Test | 8% | — |
| 2 | 2 - Exercise | Exercise | 2% | — |
| 3 | 3 - Project | Project | 30% | — |
| 4 | 4 - Examination | Examination | 60% | Threshold |
Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.
Requisites
prerequisite
- ETB2111 — Business data modelling
- ETC1010 — Introduction to data analysis
- ETC2410 — Introductory econometrics
- ETC2420 — Statistical thinking
- ETC3440 — Introductory econometrics
- ETF2020 — Statistical foundations of business analytics
- ETF2100 — Introductory econometrics
- ETF2121 — Data analysis in business
- ETW2001 — Foundations of data analysis and modelling
- ETW2510 — Introduction to econometrics
- ETX2250 — Data visualisation and communication
- ETC2560 — Statistical modelling for actuarial studies
- FIT2086 — Modelling for data analysis
- ETX2100 — Introductory econometrics
Joined by OR.
Learning outcomes
- develop statistical skills for analysing data in a business environment
- learn how to build accurate and robust models for forecasting
- acquire computer skills vital for forecasting business and economic data.
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 |
| Seminars | 12 hours |
| Tutorials | 12 hours |
Ask about ETF3231
Answered from the Handbook fields above — no AI, no guessing. Every answer links back to the source.
Community discussions about ETF3231
CommunityStudent experience, not official rules. Nothing here changes what the Handbook says.