ETF2121 Data analysis in business
Faculty of Business and Economics
ETF2121 Data analysis in business 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, FIT1006, ETC1000, SCI1020, ETF1100, STA1010, ETW1001 or ETX1100 and unlocks 4 units, leading on to 10 units in all.
- Credit points
- 6
- Offered in 2026
- Semester 1, Semester 2
- Caulfield
- Assessment
- Exam 50%
- and 2 other tasks
- Workload
- 144 hours
- per semester
This is the 2026 handbook entry. See the 2027 entry.
Reviews
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Requisites
Before ETF2121
Prohibitions
You can't enrol if you have passed any of these.
Prerequisites
Pass these before you enrol.
- ETB1100Business statisticsNo reviews yet
- FIT1006Business information analysisNo reviews yet
- ETC1000Business and economic statisticsNo reviews yet
- SCI1020Introduction to statistical reasoningNo reviews yet
- ETF1100Business statisticsNo reviews yet
- STA1010Statistical methods for scienceNo reviews yet
- ETW1001Introduction to statistical analysisNo reviews yet
- ETX1100Business statisticsNo reviews yet
After ETF2121
4 units list ETF2121 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
This unit provides an overview of fundamental tools of data and statistical analysis used in the Business and Economics disciplines. The methods covered are widely used in industry and academia, providing the necessary foundation for more advanced approaches as you advance your training and career. This unit delves deeper into basic statistical concepts, with a focus on their application in finance, accounting, and other sectors. It introduces cutting-edge software and programming languages such as R, Power-BI and SQL for robust data analysis and predictive modelling. You will engage with modern data sources and advanced sampling techniques, learn to perform hypothesis testing, and apply modelling techniques such as regression and time series analysis in business contexts. The unit places a strong emphasis on practical applications, aiming to equip you with the skills to interpret and leverage statistical data for solving business problems and making informed decisions in industry.
Offerings in 2026
| Teaching period | Campus | Mode |
|---|---|---|
| First semester | Caulfield | Blended |
| Second semester | Caulfield | Blended |
Assessment
- Quiz / Test10%
- Written40%
- Examination50%
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
apply industry-standard tools, including R, Power BI, and SQL, to query, process, analyse, visualise, and model data for business insights
- 2
implement statistical and machine learning techniques to identify patterns, generate predictions, and support data-driven decision-making
- 3
interpret and effectively communicate statistical findings to address complex business challenges and inform strategic decisions.
Workload and teaching
- Tutorials12 hours
- Workshops12 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
ETF2121 is part of 2 areas of study in the 2026 handbook.
Contacts
- Chief Examiners
- Dr Joan Tan
- Dr Hsein Kew
Common questions
What are the prerequisites for ETF2121?
You need ETB1100, FIT1006, ETC1000, SCI1020, ETF1100, STA1010, ETW1001 or ETX1100 before you enrol. Enrolment rules also apply.
What can I take after ETF2121?
ETF2121 is a prerequisite or corequisite for 4 units, including ETC3550, ETC5550, ETF3231 and ETF5231. Those lead on to 10 units in all.
When is ETF2121 offered?
In 2026, ETF2121 runs in Semester 1 and Semester 2 at Caulfield.
How much work is ETF2121?
The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.
Does ETF2121 have an exam?
Yes. The exam is worth 50% of the final mark, alongside 2 other tasks.
Which majors and minors include ETF2121?
ETF2121 is part of Business analytics and statistics.