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Data Analysis for International Relations


Credits: 4 ECTS

First semester, Second semester

Elective Courses




Data Analysis for International Relations allows students to learn fundamental skills and several basic and advanced research methods to analyze quantitative data. The course considers both the analytical logic of the methods and their practical application using statistical software. It provides students with the analyst capabilities commonly demanded in jobs that require understanding and performing quantitative data analysis.  Students enrolled in the course do not need to have a previous background on statistical or quantitative knowledge.

Students start learning about the creation and management of datasets, various descriptive statistical analyses, and the computation and interpretation of significance tests. The course continues with basic and advanced OLS regression analysis, logistic regression for binary outcomes and factor analysis.

Datasets will be provided in the course to practice the methods learned (World Values Survey, Word Bank’s World Development Indicators).  The course exercises illustrate various international relations and development topics, including economic growth analysis using longitudinal OLS regression models.  The course enables students to apply the methods taught in the course to analyze data referred to their Master’s tesina.


The course consists of 12 class sessions of two hours each, held in a computer lab. The class sessions present the explanation of the concepts and analytical tools considered in the course and their practical application using statistical software. Handouts of course notes will be distributed in class. These highly facilitate the understanding and progress of all students along the course, regardless of their initial competence level. Students need to complement the handouts attending the class explanations and consulting specific pages of the reference bibliography.

The evaluation of students is based on on their active class participation and a take-home exercise that considers the different topics learned during the course. The take-home exercise can be completed along the semester and will be submitted at the end of the course. The final grade combines the two evaluation components according to these percentages: take-home exercise (80%); active class participation (20%).

Competences, learning outcomes and teaching activities (PDF)