After this course;
- students should be able to clean, aggregate and explore data
- students should be able to use the appropriate (multivariate) statistical methods to support strategic and tactical marketing decisions
- students should compare the objectives, principles and assumptions of selected multivariate methods
- students should be able to identify proper methods to solve marketing problems on hand and argue why
- students should be able to evaluate the empirical fit of a model
- students should be able to apply multivariate methods/solve marketing problems using SPSS
- students should be able to translate the model results in plain English.
This course is offered in block 1 and in block 3. This course prepares students for the more advanced research courses in the MSc Marketing Management and MSc Marketing Research program. As a consequence, students entering the MSc program in block 1, should take the block 1 (fall) course. Students entering the MSc program in block 3, should take the block 3 (spring) course. Note that students are only allowed to follow this course 1 time per cohort, with the exam and resit associated with the course from the respective block. Students get 2 exam chances a year (and not 4).
Lecture sessions are attended by the whole group of students simultaneously. For the instruction sessions, this group of students is broken down into smaller subgroups. Students can enroll in one of the subgroups before the start of the course (the deadline for enrollment is announced online). Once enrolled in a session, students have to participate in that particular session.
Each instruction session is followed by an assignment. Participation in the assignments is mandatory. Students who have not participated in the assignments will not get a course grade.
Exams and Grading
Course grading is as follows:
Students should obtain at least 5 (on 10) for each part in order to pass the course.The exam is a closed book exam.
- Written exam (80%)
- Case-related assignment questions (together 20%)
Repeaters have to participate again in the assignments and the exams. There are no exemptions, there is no transfer of assignment or exam grades.
The course comprises 'theoretical' sessions and practical sessions/assignments. The 'theoretical' part consists of lectures, accompanied by course materials to be studied by the students. During these lecture sessions, after some guidelines for preliminary data analysis; students get in depth explanations and examples for a set of multivariate methods: Cluster analysis, Factor analysis, Multidimensional Scaling, ANOVA, Logistic Regression and Conjoint analysis. The practical part of the course involves the use of these methods on case datasets, using SPSS, where attention is paid to the type of inputs required, proper instructions to carry out and validate the different multivariate analyses, and interpretation of the various SPSS outputs.
Type of instructions
Lectures + Interactive sessions
Type of exams
Written Closed Book Exam + Assignments
- Selected chapters (indicated at the start of the course) from Hair, Black, Babin, Anderson, Tatham, Multivariate Data Analysis, Prentice Hall, 2014 (see: Course materials).
|Slides made available online by the instructor prior to the start of the course.|
|Hair, Black, Babin, Anderson (2014), Multivariate Data Analysis, Pearson New International Edition, (ISBN 13: 978-1-292-02190-4, or ISBN 10: 1-292-02190-X), seventh edition. Hereafter, the book is referred to as HBBA.|