- 3 hours teaching per week consisting of: 1 × 1-hour lecture (online) and 1 × 2-hour tutorial (lab session or online). Tutorials commence in Week 1.
- The timetable for classes can be found on the university website at: http://timetable.mq.edu.au
Required and Recommended Texts and/or Materials
- Joseph F Hair, Barry J. Babin, Rolph E. Anderson and William C. Black (2018) Multivariate Data Analysis, 8th Edition. Cengage. ISBN: 9781473756540
- Andrew F. Hayes (2018) Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach, 2nd Edition. Guilford Publications. ISBN: 9781462534654
- J. Scott Long and Jeremy Freese (2014) Regression Models for Categorical Dependent Variables Using Stata, 3rd Edition. Stata Press. ISBN: 9781597181112
- Philip Hans Franses and Richard Paap (2010) Quantitative Models in Marketing Research. Cambridge University Press. ISBN: 9780511753794
- James H. Myers and Gary M. Mullet (2003) Managerial Applications of Multivariate Analysis in Marketing. South-Western Educational Pub. ISBN: 9780877573012
- Zhao, X., Lynch Jr, J. G., & Chen, Q. (2010). Reconsidering Baron and Kenny: Myths and truths about mediation analysis. Journal of Consumer Research, 37(2), 197-206.
- Bergkvist, L., & Rossiter, J. R. (2007). The predictive validity of multiple-item versus single-item measures of the same constructs. Journal of Marketing Research, 44(2), 175-184.
- Malhotra, N. K. (1984). The use of linear logit models in marketing research. Journal of Marketing Research, 21(1), 20-31.
- Paas, L. J., & Sijtsma, K. (2008). Nonparametric item response theory for investigating dimensionality of marketing scales: A SERVQUAL application. Marketing Letters, 19(2), 157-170.
- Rossiter, J. R. (2002). The C-OAR-SE procedure for scale development in marketing. International Journal of Research in Marketing, 19(4), 305-335.
Technology Used and Required
- Students will need to have access to a personal computer, with access to the Internet and word processor software.
- In laboratories, we will use MS-Word, MS-Excel, SPSS and Sawtooth software.
Unit Web Page
- The web page for this unit can be found at: iLearn http://ilearn.mq.edu.au
- All announcements and resources will be available on the web site. Resource materials include lecture slides, practice questions, case studies and practice exam questions for both the within-semester and final exams. There is also a forum for student interaction and contact with faculty. You should consult the course Website several times per week for messages and updates.
Teaching and Learning Strategy
This unit is aimed at students who have developed higher levels of strategic insight and who desire improved skills in data manipulation, analysis and presentation. This is a predominantly applied course, designed to provide students with technical and analytical skills. Lecture attendance is critical, as it is only by attending lectures that students will understand the concepts used in tutorials. Tutorials are held in PC Labs and provide an opportunity to practice analytics hands-on using MS-Excel and Tableau software. The limited time in class is not sufficient to learn all that we will need to develop some competence in the software and methods discussed and examined. Students will need to practice and research outside of the classroom.
Satisfactory Completion of Unit
It is normally expected that students attempt all assessment tasks for this unit. Students are required to accumulate at least 50% of the total marks possible in order to satisfactorily pass this unit.