ETC3500 - Survey data analysis

Leader: Dr Neil Diamond and Professor Felix Mavondo

Offered

Clayton Second semester 2008 (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 subject and students will apply the techniques to a variety of practical problems.

Objectives

The learning objectives of this unit are to:

• examine exploratory factor analysis and structural equation modelling;
• explain how multiple regression and multivariate analysis of covariance can be used to analyse survey data;
• examine the use and importance of logistic regression in discrete-choice modelling studies;
• critically analyse the role of cluster analysis and multidimensional scaling and correspondence analysis in understanding multivariate data;
• apply a statistical package (SPSS) to a range of data.

Assessment

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

Contact hours

Two 1-hour lectures and one 2-hour tutorial per week

Prerequisites

At least one of ETC2400, ETC2410, ETC2430, ETC2450, ETC/MKC2500

Prohibitions

MKC3500/ETF3500/MKF3500/ETC4350