ETF5912 Data analysis in business
Faculty of Business and Economics
ETF5912 Data analysis in business is a level 5, 6-credit-point, postgraduate unit from the Faculty of Business and Economics, offered in 2027 in Semester 1 and Semester 2 at Caulfield. It needs ETB1100, ETC1000, ETC5900, ETF1100, ETF5900, ETM5900, ETW1001, FIT1006, SCI1020, STA1010, ETX1100 or ETX5900 and unlocks 3 units, leading on to 6 units in all.
- Credit points
- 6
- Offered in 2027
- Semester 1, Semester 2
- Caulfield
- Assessment
- Exam 50%
- and 2 other tasks
- Workload
- 144 hours
- per semester
Reviews
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Requisites
Before ETF5912
Prohibitions
You can't enrol if you have passed any of these.
Prerequisites
Pass these before you enrol.
- ETB1100Business statisticsNo reviews yet
- ETC1000Business and economic statisticsNo reviews yet
- ETC5900Business statisticsNo reviews yet
- ETF1100Business statisticsNo reviews yet
- ETF5900Business statisticsNo reviews yet
- ETM5900Business 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
- ETX5900Business statisticsNo reviews yet
After ETF5912
3 units list ETF5912 as a prerequisite or corequisite.
Enrolment rules
If you are enrolled in course B6001, there is no prerequisite.
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 2027
| Teaching period | Campus | Mode |
|---|---|---|
| First semester | Caulfield | Blended |
| Second semester | Caulfield | Blended |
Assessment
- Exercise10%
- Portfolio40%
- 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
- Workshops12 hours
- Seminars24 hours
- Tutorials12 hours
- Teaching approachActive learning
- Teaching approachProblem-based 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 engages you in actively applying your knowledge, skills and attributes in interactive, collaborative and reflective 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.
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
ETF5912 is part of 2 areas of study in the 2027 handbook.
Contacts
- Chief Examiners
- Dr Hsein Kew
- Dr Joan Tan
Common questions
What are the prerequisites for ETF5912?
You need ETB1100, ETC1000, ETC5900, ETF1100, ETF5900, ETM5900, ETW1001, FIT1006, SCI1020, STA1010, ETX1100 or ETX5900 before you enrol. Enrolment rules also apply.
What can I take after ETF5912?
ETF5912 is a prerequisite or corequisite for 3 units, including ETC5550, ETF5231 and ETX5500. Those lead on to 6 units in all.
When is ETF5912 offered?
In 2027, ETF5912 runs in Semester 1 and Semester 2 at Caulfield.
How much work is ETF5912?
The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.
Does ETF5912 have an exam?
Yes. The exam is worth 50% of the final mark, alongside 2 other tasks.
Which majors and minors include ETF5912?
ETF5912 is part of Data analytics for business and Financial analytics.