ETX2250 Data visualisation and analytics
Faculty of Business and Economics
ETX2250 Data visualisation and analytics is a level 2, 6-credit-point, undergraduate unit from the Faculty of Business and Economics, offered in 2025 in Summer A and Semester 2 at Caulfield. It needs ETF1100, STA1010, ETW1001, ETX1100, ETB1100, FIT1006, ETC1000 or SCI1020 and unlocks 6 units, leading on to 10 units in all.
- Credit points
- 6
- Offered in 2025
- Summer A, Semester 2
- Caulfield
- Assessment
- Exam 50%
- and 2 other tasks
- Workload
- 144 hours
- per semester
This is the 2025 handbook entry. See the 2027 entry.
Reviews
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Requisites
Before ETX2250
Prerequisites
Pass these before you enrol.
- ETF1100Business statisticsNo reviews yet
- STA1010Statistical methods for scienceNo reviews yet
- ETW1001Introduction to statistical analysisNo reviews yet
- ETX1100Business statisticsNo reviews yet
- ETB1100Business statisticsNo reviews yet
- FIT1006Business information analysisNo reviews yet
- ETC1000Business and economic statisticsNo reviews yet
- SCI1020Introduction to statistical reasoningNo reviews yet
Prohibitions
You can't enrol if you have passed any of these.
After ETX2250
6 units list ETX2250 as a prerequisite or corequisite.
- ETF3231Business forecastingNo reviews yet
- ETF3500High dimensional data analysisNo reviews yet
- ETF5231Business forecastingNo reviews yet
- ETF5500High dimensional data analysisNo reviews yet
- ETF5932Predictive analytics and machine learningNo reviews yet
- ETX3250Predictive analytics and machine learningNo reviews yet
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
Business analytics can unlock the hidden insights in data to give businesses a competitive advantage. Many businesses have masses of data about customers and operations, and need skilled analysts to uncover insights and make informed predictions.
This unit uses data visualisation to explore and analyse data sets of all sizes, and it introduces some business analytic models for interpretation and prediction.
It will introduce an appropriate software environment for data visualisation, and analytics, and cover visualisation and analysis techniques for categorical and numerical variables. Visualisation methods to be covered include some of Box-and-whisker plots, Mosaics, Rotatable 3D scatter plots, Heat maps, Motion charts, cluster and association charts. Models to be covered may include linear regression models, classification and regression trees, and random forests. Methods for evaluating model performance will also be discussed. Examples from marketing, finance, economics and related disciplines will be included.
Offerings in 2025
| Teaching period | Campus | Mode |
|---|---|---|
| Summer semester A | Caulfield | On campus |
| Second semester | Caulfield | On campus |
Assessment
- Quiz / Test10%
- Written40%
- Examination50%
Learning outcomes
When you finish this unit, you should be able to:
- 1
select, create and interpret appropriate types of visual representation for a given set of data
- 2
select and develop model types with explanatory and/or predictive ability
- 3
make appropriate use of in-sample and out-of-sample evaluation of models
- 4
apply the above research skills to produce innovative solutions in finance, marketing, economics and related areas
- 5
use visualisation and modelling to effectively communicate the results of their investigations
- 6
explain the sequence of procedures that should be applied to analyse a given dataset.
Workload and teaching
- Workshops12 hours
- Workshops36 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
ETX2250 is part of 3 areas of study in the 2025 handbook.
Contacts
- Chief Examiners
- Shanika Wickramasuriya
- Kate Saunders
Common questions
What are the prerequisites for ETX2250?
You need ETF1100, STA1010, ETW1001, ETX1100, ETB1100, FIT1006, ETC1000 or SCI1020 before you enrol. Enrolment rules also apply.
What can I take after ETX2250?
ETX2250 is a prerequisite or corequisite for 6 units, including ETF3231, ETF3500, ETF5231, ETF5500, ETF5932 and ETX3250. Those lead on to 10 units in all.
When is ETX2250 offered?
In 2025, ETX2250 runs in Summer A and Semester 2 at Caulfield.
How much work is ETX2250?
The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.
Does ETX2250 have an exam?
Yes. The exam is worth 50% of the final mark, alongside 2 other tasks.
Which majors and minors include ETX2250?
ETX2250 is part of Business analytics and statistics; and Financial econometrics.