ETF3500 - Survey data analysis

Leader(s): Dr Ann Maharaj

Offered

Caulfield Second semester 2009 (Day)

Synopsis

This unit adopts a very practical approach to introducing multivariate statistical techniques that are currently popular in the analysis of business survey data. The main topics to be covered are: a review of statistical tools, factor analysis, structural equation modelling, cluster analysis, discriminant analysis, correspondence analysis and multivariate analysis of variance. SPSS software will be used for problem solving. The emphasis will be on understanding, interpreting and reporting results of the analysis and on the proper use of techniques. Case studies drawn from business will be discussed.

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: 50%
Examination (2 hours): 50%

Contact hours

One 2-hour lecture and one 1-hour laboratory session per week

Prerequisites

ETX2121, ETX2111 or MKF2121

Prohibitions

ETC3500, MKC3500 and MKF3500