6 ECTS credits
150 h study time

Offer 1 with catalog number 1021441CER for all students in the 2nd semester at a (C) Bachelor - specialised level.

Semester
2nd semester
Enrollment based on exam contract
Possible
Grading method
Grading (scale from 0 to 20)
Can retake in second session
Yes
Enrollment Requirements
Students must have taken ‘Quantitative Research Methods’, before they can enroll in this course.
Taught in
English
Partnership Agreement
Under interuniversity agreement for degree program
Faculty
Faculty of Social Sciences & SolvayBusinessSchool
Department
Sociology
External partners
Universiteit Gent
Educational team
Amelie Van Pottelberge (course titular)
Activities and contact hours
39 contact hours Lecture
111 contact hours Independent or External Form of Study
Course Content

This main objective of this methodological course is to introduce students to a number of multivariate techniques most commonly used in the social sciences. As such, this course builds on the knowledge and skills acquired in the educational components ‘Statistics for the Social Sciences’ (1BA) and ‘Quantitative Research Methods’ (2BA). While some attention is spent on the statistical-mathematical background of these techniques, there is a special emphasis on the practical application of the techniques, so that, upon completion of the course, the students have the competences to choose among the discussed techniques the correct one(s) to tackle complex social science research questions, to perform the chosen technique(s) adequately, and to interpret the results in a sound manner.

Specifically, the course deals with four groups of techniques

  1. Exploratory Factor Analysis and Principal Components Analysis (PCA);
  2. Logistic regression analysis 
  3. Analyses of Variance (ANOVA) and CoVariance (ANCOVA), Multivariate Analysis of Variance (MANOVA);
  4. Multivariate linear regression analysis

For every method, lectures where the method is introduced are followed by laboratory sessions, in which students are trained in hands-on exercises using statistical computer software (e.g., SPSS).

Course material
Digital course material (Required) : Reader - to be communicated at start of the course
Additional info

Didactic forms

  • Interactive lectures with class discussions, peer-to-peer learning;
  • E-learning;
  • Seminar with guided PC-exercises;
  • Guided self-study
Learning Outcomes

General Competences

Upon completion of this course, students will have learned the following competencies

  • To explain in their own words the basic principles of each of the taught techniques in multivariate data analysis
  • To understand, interpret, and critically assess published results of advanced statistical techniques in social science literature
  • To make a responsible choice between advanced research techniques to answer complex research questions
  • To test the assumptions and discuss the limitations of advanced research techniques
  • To design and carry out adequately advanced statistical analyses on social science data
  • To interpret and report the results of complex statistical analyses properly

More generally, the course addresses the following program learning objectives:

  • L07: knows the methods of data selection, management and analysis that prevail within the domains of the social sciences.
  • LO10: can critically position their research against the theories that prevail in the international social sciences literature, including recent developments and innovations in these literatures
  • LO11: can, independently, identify, gather and critically process relevant sources and literature on a specific social sciences research topic.
  • LO12: can, with limited supervision, apply social theories and concepts to a well-delineated, socially and scientifically relevant research topic in the domain of the social sciences.  
  • LO13: can, with limited supervision, formulate a valid scientific research question on a social sciences research topic.  
  • LO14: can, with limited supervision, set up a scientific and methodologically correct research design to answer a research question in the domain of the social sciences.  
  • LO15: can, with limited supervision, perform the necessary methodological steps (data selection, processing and management, and analysis) to answer a research question on a social sciences research topic.
  • LO16: can report, independently, on their research in both oral and written form.  
  • LO17: can work in team and collaborate with peers in a relationship of mutual respect.
  • LO18: can reflect on and evaluate their learning process and research and can deal with criticism in a constructive manner.  
  • LO19: treats the intellectual property of others with respect and integrity

Grading

The final grade is composed based on the following categories:
Written Exam determines 100% of the final mark.

Within the Written Exam category, the following assignments need to be completed:

  • Exam with a relative weight of 100 which comprises 100% of the final mark.

Additional info regarding evaluation

The written exam is composed of two parts. The first part involves both theoretical and practical open questions. For the second part, students will solve practical questions with the help of computer software, including SPSS. This exam targets insight in rather than reproduction of the subject matter. 

Allowed unsatisfactory mark
The supplementary Teaching and Examination Regulations of your faculty stipulate whether an allowed unsatisfactory mark for this programme unit is permitted.

Academic context

This offer is part of the following study plans:
Bachelor of Social Sciences: Communication Studies
Bachelor of Social Sciences: Political Sciences
Bachelor of Social Sciences: Sociology