ETF2020 Statistical foundations of business analytics
Faculty of Business and Economics
ETF2020 Statistical foundations of business analytics is a level 2, 6-credit-point, undergraduate unit from the Faculty of Business and Economics, offered in 2026 in Semester 1 and Semester 2 at Caulfield. It needs ETB1100, ETC1000, ETF1100, ETW1001, FIT1006, SCI1020, STA1010 or ETX1100 and unlocks 5 units, leading on to 9 units in all.
- Credit points
- 6
- Offered in 2026
- Semester 1, Semester 2
- Caulfield
- Assessment
- Exam 60%
- and 1 other task
- Workload
- 144 hours
- per semester
This is the 2026 handbook entry. See the 2027 entry.
Reviews
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Requisites
Before ETF2020
Prerequisites
Pass these before you enrol.
- ETB1100Business statisticsNo reviews yet
- ETC1000Business and economic statisticsNo reviews yet
- ETF1100Business statisticsNo reviews yet
- ETW1001Introduction to statistical analysisNo reviews yet
- FIT1006Business information analysisNo reviews yet
- SCI1020Introduction to statistical reasoningNo reviews yet
- STA1010Statistical methods for scienceNo reviews yet
- ETX1100Business statisticsNo reviews yet
Prohibitions
You can't enrol if you have passed any of these.
After ETF2020
5 units list ETF2020 as a prerequisite or corequisite.
Enrolment rules
To be successful in this unit, background knowledge and application of maths is required at the equivalent of VCE Year 12 level. You may have satisfied this by completing relevant prerequisite unit/s, or you have covered relevant topics in your final years of secondary study. You should self-assess your maths competency prior to enrolling in this unit.
Equivalent units
The same content under another code. Only one of them counts.
Overview
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 in 2026
| Teaching period | Campus | Mode |
|---|---|---|
| First semester | Caulfield | Blended |
| Second semester | Caulfield | Blended |
Assessment
- Written40%
- Examination60%
Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.
Learning outcomes
When you finish this unit, you should be able to:
- 1
think and communicate about risk in a probabilistic way and apply this thinking to a business problem
- 2
understand random variables, statistical distributions and conditional probability
- 3
appreciate how conditional probabilities can be misinterpreted in business settings and how this is overcome with Bayes’ Rule
- 4
frame a business problem using probability and statistics and make data-driven decision in the presence of risk
- 5
apply the main methods of statistical estimation, prediction and inference and evaluate their properties
- 6
evaluate and choose between different statistical models.
Workload and teaching
- Workshops12 hours
- Tutorials12 hours
- Seminars24 hours
- Teaching approachProblem-based learning
- Teaching approachActive learning
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.
This unit includes problem-based learning approaches, where you engage in research, integrate theory and practice and apply knowledge and skills to develop viable solutions in response to a problem or set of problems.
This unit engages you in actively applying your knowledge, skills and attributes in interactive, collaborative and reflective activities.
Learning resources
Technology resources
There may be an additional cost associated with purchasing a physical and/or virtual calculator. Specific details will be provided in the Learning Management System by commencement of Orientation week.
Where it fits
ETF2020 is part of 2 areas of study in the 2026 handbook.
Contacts
- Chief Examiners
- Professor Bin Peng
- Dr Nikolas Kuschnig
Common questions
What are the prerequisites for ETF2020?
You need ETB1100, ETC1000, ETF1100, ETW1001, FIT1006, SCI1020, STA1010 or ETX1100 before you enrol. Enrolment rules also apply.
What can I take after ETF2020?
ETF2020 is a prerequisite or corequisite for 5 units, including ETF3231, ETF5231, ETX3250, ETX3500 and ETX5500. Those lead on to 9 units in all.
When is ETF2020 offered?
In 2026, ETF2020 runs in Semester 1 and Semester 2 at Caulfield.
How much work is ETF2020?
The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.
Does ETF2020 have an exam?
Yes. The exam is worth 60% of the final mark, alongside 1 other task.
Which majors and minors include ETF2020?
ETF2020 is part of Business analytics and statistics.