ETF5500 - Survey data analysis

Leader(s): Dr Ann Maharaj

Offered

Caulfield Second semester 2009 (Day)

Synopsis

Adopts a very practical approach to introducing multivariate statistical techniques currently popular in analysis of business and marketing survey data. Main topics: review of statistical tools, factor analysis, structural equation modelling, cluster analysis, discriminant analysis, correspondence analysis and multivariate analysis of variance. Use of SPSS software. Case studies and exercises will be drawn from diverse areas of the business world.

Objectives

The learning goals associated with this unit are to:

• introduce exploratory factor analysis and structural equation modelling
• show how multiple regression and multivariate analysis of covariance can be used to analyse survey data
• give students exposure to logistic regression in discrete-choice modelling studies
• demonstrate the role of cluster analysis and multidimensional scaling and correspondence analysis in understanding multivariate data
• provide students an opportunity to become competent in the use of a statistical package (SPSS).

Assessment

Within semester assessment: 50%
Examination (2 hours): 50%

Contact hours

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

Prerequisites

Students must be enrolled in course codes 3816 or 3822 or must have passed ETX2121, ETX2111 or MBA9007

Prohibitions

ETC3500, MKC3500, ETF3500, MKF3500