Year
2016
Units
4.5
Contact
1 x 2-hour seminar weekly
Assumed knowledge
Students should have completed BUSN1009 Quantitative Methods or equivalent.
Course context
Core topic
Assessment
Assignments, Examinations 50%, Project.
Topic description
Essential data management techniques: transformation of variables, seasonality, missing variables, frequency tables and cross-tabulation; Linear regression models; Use of dummy variables and interaction effects; Simultaneous-equation models; Time series models; Cross-sectional models; Panel data models; Logit and probit models for binary choice; Multiple choice models; Tobit models.
Educational aims
This topic aims to:

Equip students with knowledge and skills in quantitative methods which they can apply to arrange of business research problems.
Expected learning outcomes
On successful completion of this topic students should be able to:
  • Model the relations among variables and draw inferences about relations
  • Estimate different types of models using appropriate software
  • Understand and critique the data analysis of research papers
  • Prepare an individual project which features sound analysis of data and is correctly presented.