MKF3500 - Survey data analysis

Leader: Professor Felix Mavondo

Offered

Caulfield Second semester 2009 (Day)

Synopsis

Introduction to multivariate statistical techniques for the analysis of survey data and models to analyse the discrete choice behaviour of individuals. Topics include multivariate analysis of variance, principal components analysis, factor analysis, correspondence analysis and models of discrete choice behaviour. Statistical software and case studies will be utilised during this unit and students will apply the techniques to a variety of practical problems.

Objectives

The learning goals associated with this unit are to:

• 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
• appraise the strengths and limitations of these techniques
• apply tools in SPSS to generate solutions for the appropriate statistical techniques
• demonstrate skills in using the appropriate statistical techniques from a user and provider perspective
• demonstrate skills in communicating the results of the analysis so that decision making can be implemented.

Assessment

Within semester assessment: 40%
Examination (2 hours): 60%

Contact hours

3 hours class contact or equivalent per week

Prerequisites

ETX2111, ETX2121 or MKF2121

Prohibitions

ETC3500, ETF3500, MKC3500