Quantitative Methods for Information Systems

Undergraduate

Multivariate data analysis and quantitative methods in information systems and their application to business decision making. SPSS and/or other relevant statistical software to generate solution output. Topics include data preparation, data testing and transformation, multiple regression, principal components analysis, common factor analysis, multiple discriminant analysis, multiple and logistic regression and multivariate analysis of variance. Introduction to structural equation modelling, hierarchical linear modelling, canonical correlation or multidimensional scaling. Course Format: Lectures, lab, 3 hours per week. Restrictions: Open to BAcc, BBA, BCB, Data Sciences and Analytics majors (DASA/DAFA) and combined Business majors. Prerequisite(s): ITIS 2P91 or ACTG 3P97; MATH 1P97 and STAT 1P98 (MATH) Course Notes: This course may be offered in multiple modes of delivery. The method of delivery will be listed on the academic timetable, in the applicable term.