Quantitative Business Research Methods I (RBUS6902)
Information valid for Semester 2, 2025
Course level
Undergraduate
Faculty
School
Business School
Units
2
Duration
One Semester
Attendance mode
In Person
Class hours
Seminar 3 Hours/ Week
Restricted
Restricted to students in the BAdvBus(Hons), BBusMan(Hons), GCBA, GDipBRM, MBA, MPhil and PhD programs. To enrol: BAdvBus(Hons) students must email bel@uq.edu.au; MBA students must email mba@business.uq.edu.au; all other students must email info@business.uq.edu.au Quota: Min. 10 enrolments.
Course enquiries
Professor Peter Popkowski-Leszczyc (Semester 1, Semester 2, Regular, St Lucia, In person)
Current course offerings
Course offerings | Location | Mode | Course Profile |
Semester 1, 2025 (24/02/2025 - 21/06/2025) | St Lucia | In Person | Course Profile |
Semester 2, 2025 (28/07/2025 - 22/11/2025) | St Lucia | In Person | Profile unavailable |
Please Note: Course profiles marked as not available may still be in development.
Course description
Students will be exposed to a key element of the research process - data analysis. They will gain hands-on skills to analyze quantitative data and offer solutions to the research questions posed. This course provides students with an introduction to the fundamentals of multivariate data analysis. Students will acquire skills in the analysis of multivariate data from experimental and survey designs commonly used in business research. The course mainly deals with the techniques of analysis of variance, multiple regression analysis and factor analysis, and with their specific application to research in the applied business disciplines (eg. accounting, business information systems, international business, management, marketing, etc.). Emphasis is placed on the concepts and statistical theory of multivariate data analysis, along with a refresher on the basics of univariate analysis: descriptive and inferential statistical procedures. This practical and applied course is lab-based with a mix of short seminar style presentations and instruction in the use of statistical packages for specifying and estimating models involving multivariate data analysis.