Statistical Marketing Tools
HMS794
Overview
To enrol in this unit, you must be accepted into a course from the provider.
Read before you start
Level of study: What does Postgraduate mean?
Postgraduate
EFTSL: What does EFTSL mean?
0.125
Delivery Method: What does delivery method mean?
Web Dependent
Prerequisites: What are the prerequisites?
Duration:
13 weeks
Government loans available:
FEE-HELP FEE-HELP
Domestic student fee:
$1,950.00 (AUD)
International student fee:
$2,175.00 (AUD)
Description
This unit is designed to investigate the underlying structure of market research and social science data using a number of dimensional analysis mapping, segmentation and preference techniques. This subject is of particular importance for market research analysts in both commerce and industry. The process of datamining is introduced as well as most of the techniques used by data miners. These approaches are illustrated using real life examples drawn from various data rich environments.
Enrolment Restriction
In order to enrol in this unit, you must be accepted into one of the following courses:
If you wish to seek approval to enrol in this unit without being accepted in a course, please contact OUA regarding the process.
Prerequisites
Recommended prerequisites
You are recommended to have completed the following unit(s) or have equivalent knowledge before starting this unit:
- HMS770 — Statistical Practice 1
- HMS771 — Statistical Practice 2
- HMS780 — Multivariate Statistics
Special Requirements
- Additional materials
- 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.
Assessment
- Assignment 1 (20%)
- Assignment 2 (20%)
- Invigilated Exam (50%)
- Quizzes (10%)
Learning Outcomes
At the completion of this unit students will be able to:
- demonstrate an understanding of the basic theory and principles of data mining
- perform and interpret association analyses including market segmentation and market basket analysis
- apply prediction and classification methods such as regression, neural networks and decision trees, understanding how to choose between these methods
- use quantitative analsis techniques commonly used in market research.
- use mapping techniques including multi-dimensional scaling and correspondence analysis
- use preference techniques including conjoint analysis
- read, understand and critically assess research publications which use data mining methods and statistical tools for marketing.
Topics
This unit addresses the following topics.
| Number | Topic |
|---|---|
| 1 | Mapping techniques inclduing multi-dimensional scaling and correspondence analysis |
| 2 | Preference techniques including conjoint analsis |
| 3 | Market segmentation methods |
| 4 | Data mining approaches and procedures using appropriate software |
| 5 | Association using market basket analysis and link analysis |
| 6 | Regression trees and linear regression |
| 7 | Clustering with SAS enterprise miner |
| 8 | Clustering with SPSS |
| 9 | Classification using logistic regression, classification trees, neural networks and memory based reasoning |
| 10 | Prediction using regression, regression trees, neural networkds and memory based reasoning |
Study Resources
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
Textbook information for this unit is currently being updated and will be available soon. Please check back regularly for updates. Alternatively, visit the Unibooks website and enter the unit details to search for available textbooks.
Relevant Courses
This unit is a core requirement in the following courses:
This unit may be eligible for credit towards other courses:
- 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.
- 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 Unibooks textbook list.
