The Master of Science in Social Scientific Data Analysis will prepare you to become a professional researcher/social scientific data analyst with a specialisation on the research process and research methodology. Coursework involves extensive and intensive training in the process of conducting social research, research design, methodology, qualitative and quantitative methods (students are taught to program using state-of-the-art statistical software ’R’), as well as applied theory, theory building, and a range of interdisciplinary theories.
As a graduate, you will be well suited for two complementary job markets: as data analysts, researchers, and research project managers within the private and public spheres, and civil society, as well as PhD candidate-ships within academia.
The Research Process, 15 credits (first half of the first term)
Introduction to Quantitative Methods Using R, 15 credits (second half of the first term)
Using Social Theory, 7.5 credits (part one of the first half of the second term)
Intermediate Quantitative Methods Using R, 7.5 credits (part two of the first half of the second term)
Two Qualitative Elective Courses, 15 credits, (second half of the second term)
Disciplinary Elective Period, 15 credits (first half of the third term)
Advanced Theory Elective, 7.5 credits (part one of the second half of the third term)
Advanced Methods Elective, 7.5 credits (part two of the second half of the third term)
Master’s thesis in the student’s major social science discipline, 30 credits (the fourth term)
The programme will train students with the following qualifications:
A. the professional researcher, analyst and research manager: professional researchers skilled in a variety of methods, to include at least intermediate to advanced quantitative and qualitative methods. Methods and methodological skills will allow researchers not only to conduct research but also will allow them to better assess and use existing studies as evidence for policy/programme design. An in-depth understanding of the method used in a study allows students to immediately see flaws and opportunities for improvement of the evidence base for the policy/programme an organisation is developing. Ideal labour markets here would be ’data science’ with social scientific training (e.g. conducting data analysis, market research for research organisations, IT companies, general organisational consultancies, risk management firms, intelligence analysis, or other private companies).
B. the PhD candidate with strong methodology training linked to both methods and theory: training students who would like to apply for an international PhD position and learn a certain type of applicable skills (methods, methodology, research design, meta-theory, using social theory).
In addition to the above-mentioned skills, students will also learn programming skills (in ’R’, a flexible, powerful, and open-source statistical software) and research publishing skills.