This Statistical Marketing Tools unit from Open Universities Australia and Swinburne University of Technology focuses on the basic theory and principles of data mining.
After successfully completing this unit, you will be able to assess prediction and classification methods such as regression, neural networks and decision trees, and understand how to choose between these methods.
You will also be able to evaluate unsupervised data mining methods and evaluate when these methods should be combined with supervised methods. This unit requires you to compose a detailed report and presentation about a specific data mining project.
You cannot enrol in this unit if you have completed any unit deemed academically equivalent.
To be eligible for this unit, you must have successfully completed one of the following units:
You will require access to a recent version of SPSS. You will also be asked to sign and return an agreement form in order to obtain a free copy of SAS 9.2. Note: SAS will only run on a Windows platform. In order to enrol in this unit, you must be accepted into the following course:
Master of Science (Applied Statistics)
Areas of study
In this Statistical Marketing Tools unit, the topics you will study include:
Mapping techniques including multi-dimensional scaling and correspondence analysis
Preference techniques including conjoint analysis
Market segmentation methods
Data mining approaches and procedures using appropriate software
Association using market basket analysis and link analysis
Regression trees and linear regression
Clustering with SAS enterprise miner
Clustering with SPSS
Classification using logistic regression, classification trees, neural networks and memory based reasoning
Prediction using regression, regression trees, neural networks and memory based reasoning
This unit is a core requirement in the following course:
Master of Science (Applied Statistics), Swinburne University of Technology
Content may also be relevant to other courses, and could qualify you for Recognition of Prior Learning (RPL) for a course offered by another institution.
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The unit is of particular importance for market research analysts in both commerce and industry. Core competencies include data mining skills, analysis and techniques, as well as the ability to design creative visualisation techniques to display relationships in any context.
How else will I benefit from this unit?
Upon successful completion of this unit you will receive credit for competencies in Statistical Marketing Tools from Swinburne University of Technology.
Studying online means you can study where you want, at your own pace.
Gain industry-relevant skills and transferrable knowledge.
Government financial support through FEE-HELP may be available.
Studying single units allows you the flexibility to work towards a qualification at your own pace.
Receive Recognition of Prior Learning (RPL) for this unit across a number of OUA’s full degree programs.
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Want more information about the career benefits of this unit? Fill out the enquiry form to the right and a study consultant will contact you with the details you need.
If you are an Australian citizen, you may be eligible to receive a government FEE-HELP loan, meaning you can defer payment of your fees.
Get more information
Want more information about financial and student support? Fill out the enquiry form to the right and a study consultant will contact you with the details you need.
You may be eligible to receive FEE-HELP for this course!
This course can be paid for through the FEE-HELP government loan scheme. If you are an Australian citizen or hold a permanent humanitarian visa, this means you don’t need to pay upfront.
Instead, the Australian government will pay your course fees on your behalf. You’ll begin repaying your loan through the tax system once you start earning more than the minimum threshold of $54,869 (2016-17 income year).
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