UnitLevel 5Postgraduate

ETX5500 High dimensional data analysis

Faculty of Business and Economics

ETX5500 High dimensional data analysis 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 Clayton and Caulfield. It needs ETC1010, ETC2420, ETC3550, ETC5242, ETC5510, ETC5550, ETF3231, ETF5231, ETF5922, ETW2001, ETX2250, FIT5197, ETF2020, ETF2100, ETF5202, ETF5910, ETC2410, ETF5912, ETC5241 or ETF5912.

Credit points: 6
Offered in 2027: Semester 1, Semester 2; Clayton, Caulfield
Assessment: Exam 50%; and 2 other tasks
Workload: 144 hours; per semester

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Requisites

Before ETX5500

Prerequisites

Pass these before you enrol.

One of

Prohibitions

You can't enrol if you have passed any of these.

ETX3500High dimensional data analysisNo reviews yet

After ETX5500

No unit lists ETX5500 as a prerequisite in the 2027 handbook.

Enrolment rules

If you do not meet the prerequisite you must be granted permission by the Chief Examiner to undertake this unit.

Equivalent units

The same content under another code. Only one of them counts.

ETX3500High dimensional data analysisNo reviews yet

Overview

In many fields of business, analysts must deal with data on many variables, for example, surveys with a large number of questions. In such cases, statistical tools known as multivariate methods must be used to analyse the data and drive business decisions.

This unit covers such methods in three sections: Cluster Analysis can be used to identify and predict differences between groups such as between distinct classes of customers or products; Principal Components Analysis, Correspondence Analysis and Multidimensional Scaling are dimension reduction methods that help analysts to visualise complicated datasets; and finally, Factor Analysis is used to explain and predict business outcomes.

Offerings in 2027

Teaching period	Campus	Mode
First semester	Clayton	Blended
Second semester	Caulfield	On campus

Assessment

Project
20%
Exercise
30%
Examination
50%

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
demonstrate an understanding of the role that multivariate statistical techniques such as factor analysis, structural equation modelling, logistic regression, categorical data analysis, cluster analysis, multidimensional scaling and correspondence analysis play in uncovering relationships and patterns in survey data
2
appraise the strengths and limitations of these techniques
3
apply tools in R to generate solutions for the appropriate statistical techniques
4
demonstrate skills in using the appropriate statistical techniques from a user and provider perspective
5
demonstrate skills in communicating the results of the analysis so that decision making can be implemented.

Workload and teaching

Tutorials12 hours
Seminars24 hours
Workshops12 hours
Teaching approachCase-based teaching
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 case-based teaching, where you apply your knowledge and engage in analytical and reflective thinking to solve complex contextual scenarios. Activities are often designed so that there is not one clear answer, but you need to work together to examine, analyse and make decisions to resolve the situation.

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

ETX5500 is part of 4 areas of study in the 2027 handbook.

Contacts

Chief Examiners: Dr Shanika Wickramasuriya; Associate Professor Ole Maneesoonthorn

Common questions

What are the prerequisites for ETX5500?

You need ETC1010, ETC2420, ETC3550, ETC5242, ETC5510, ETC5550, ETF3231, ETF5231, ETF5922, ETW2001, ETX2250, FIT5197, ETF2020, ETF2100, ETF5202, ETF5910, ETC2410, ETF5912, ETC5241 or ETF5912 before you enrol. Enrolment rules also apply.

When is ETX5500 offered?

In 2027, ETX5500 runs in Semester 1 and Semester 2 at Clayton and Caulfield.

How much work is ETX5500?

The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.

Does ETX5500 have an exam?

Yes. The exam is worth 50% of the final mark, alongside 2 other tasks.

Which majors and minors include ETX5500?

ETX5500 is part of Actuarial studies, Business analytics, Data analytics for business and Econometrics.

More details

Credit points: 6
Level: 5
Study level: Postgraduate
Faculty: Faculty of Business and Economics
Organisational unit: Department of Econometrics and Business Statistics

Type: Coursework
EFTSL: 0.125
Student contribution: SCA Band 1
Study abroad: Available
Handbook years: 20262027