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High dimensional data analysis
ETX3500
Synopsis
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.
Sourced from the Monash Handbook 2026.
Quick facts
- Credit points
- 6
- Level
- 3
- Audience
- Undergraduate
- Type
- Coursework
- School
- Faculty of Business and Economics
- Faculty
- Department of Econometrics and Business Statistics
- Handbook year
- 2026
Prerequisites (9)
- Introduction to data analysisETC1010
- Introductory econometricsETC2410
- Statistical thinkingETC2420
- Applied forecastingETC3550
- Statistical foundations of business analyticsETF2020
- Introductory econometricsETF2100
- Business forecastingETF3231
- Foundations of data analysis ETW2001
- Data visualisation and communicationETX2250
What it unlocks
Nothing in the visible graph depends on this unit.
Offerings (2)
- Second semesterCaulfield · ON-CAMPUS
- First semesterClayton · BLENDED
Listed in 6 areas of study
- Actuarial analyticsCore units
- Business analyticsAdditional business analytics units
- Business analyticsAdditional business analytics units
- Business analytics and statisticsCore units
- Business analytics and statisticsSpecified discipline electives
- Financial econometricsAdditional financial econometrics units