Advanced data analysis method with fsQCA

The course introduces systematic analysis of quantitative and qualitative data with the help of fuzzy set Qualitative Comparative Analysis (fsQCA). FsQCA is an advanced mixed method which consists of an analytical technique for studying complex social phenomena. The method can be used to compare different empirical cases to find causal patterns between conditions, specifically necessary and sufficient conditions that produce a certain outcome. The method is applied in order to understand complex causal relationships between different conditions and outcomes.

The course is divided into five modules: 1) The basic principles of QCA, ii) Calibration of data, iii) Analysis of necessary conditions, iv) Analysis of sufficient conditions, and v) Presentation of results.

Students participate actively in lectures and exercises for each module. The course requires continuous reading, participation in seminars, written assignments, practical exercises, and presentations.

Progressive specialisation: A1N (has only first‐cycle course/s as entry requirements)

Education level: Master's level

Admission requirements: 90 ECTS credits, including at least 30 ECTS credits at the G2F level or higher, in the social, behavioural, or natural sciences, at least 2 years of work experience in a relevant professional area, and upper secondary level English 6 or A, or equivalent

Selection:

Selection is usually based on your grade point average from upper secondary school or the number of credit points from previous university studies, or both.