Statistical Marketing Tools - 2017

To enrol in this unit, you must be accepted into a course from the provider. Read before you start

Unit summary


  • Level of Study: Postgraduate
  • Study load: 0.125 EFTSL
  • Delivery method: Fully Online
  • Prerequisites: Yes
  • Duration: 13 weeks
  • Government loans available: FEE-HELP
  • Availability for 2017: SP3
  • Availability for 2018: SP3
  • Assessment: Assignments - 30%-40% , Invigilated Exam - 50%-60% - Learn more

Unit provided by

2017 Fees
Domestic 2,600.00
Domestic continuing 2,472.00
International 2,850.00
International continuing 2,722.00

Tuition fees are reduced for continuing registered SWI students.
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In this unit of study the aim is for students to be able to investigate the underlying structure of market research and social science data using a number of dimensional analysis mapping, segmentation and preference techniques. The process of data mining is introduced as well as most of the techniques used by data miners.

After successfully completing this unit, students will  be able to:
  1. Formulate an understanding of the basic theory and principles of data mining
  2. Assess prediction and classification methods such as regression, neural networks and decision trees, understanding how to choose between these methods
  3. Evaluate unsupervised data mining methods and evaluate when these methods should be combined with supervised methods
  4. Design creative visualisation techniques to display relationships in any context.
  5. Compose a detailed report and presentation about a specific data mining project.
  • Assignments — 30%-40%
  • Invigilated Exam — 50%-60%
  • Quizzes — 10%
For more information on invigilated exams see Exams and results

Equivalent units

You cannot enrol in this unit if you have successfully completed any of the following unit(s) because they are considered academically equivalent:

  • HMS794 — Statistical Marketing Tools

Mandatory prerequisites

You must have successfully completed the following unit(s) before starting this unit:

If you have completed equivalent study at another university, please contact a Student Advisor for advice.

  • Other special requirement — 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 one of the following courses:

Please visit the course details page and read the Requirements tab for more information about eligibility.

This unit addresses the following topics.

1Intro to data mining and SAS Enterprise Miner
2Market basket analysis, sequence analysis and link Analysis.
3Classification Trees and Logistic regression.
4Regression and regression trees.
5Neural networks for classification and prediction and clustering.
6Segmentation and Self Organising Maps
7Multidimensional scaling
8Correspondence analysis
9Cluster Analysis

This unit is delivered using the following methods and materials:

Instructional Methods

  • Discussion Forum/Discussion Board
  • Online Quizzes/Tests
  • Online assignment submission
  • Podcasting/Lecture capture
  • Standard Media
  • Web links

Print based materials

  • Welcome Letter

Online materials

  • Printable format materials

This unit is a core requirement in the following courses:

This unit may be eligible for credit towards other courses:

  1. Many undergraduate courses on offer through OUA include 'open elective' where any OUA unit can be credited to the course. You need to check the Award Requirements on the course page for the number of allowed open electives and any level limitations.
  2. In other cases, the content of this unit might be relevant to a course on offer through OUA or elsewhere. In order to receive credit for this unit in the course you will need to supply the provider institution with a copy of the Unit Profile in the approved format, which you can download here. Note that the Unit Profile is set at the start of the year, and if textbooks change this may not match the Co-Op textbook list.
This unit does not have a prescribed textbook(s).

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