Data Analysis for International Relations
Crèdits: 4 ECTS
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 (SPSS). It provides students with the analyst capabilities commonly demanded in jobs that require understanding and performing quantitative data analysis. It also allows students to apply the methods learned to analyze data referred to their Master’s tesina. Students enrolled in the course do not need to have a previous background in statistics or quantitative-mathematical 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, which are fundamental methods of data analysis in the social sciences.
Datasets will be provided in the course to practice the methods learned (World Values Survey [WVS], Word Bank’s World Development Indicators). The course exercises illustrate various international relations and development topics, including economic growth analysis using longitudinal OLS regression.
Class sessions are held in a computer lab. During the sessions, the professor explains 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 handouts highly facilitate the understanding and progress of all students along the course, regardless of their initial competence level.
The evaluation of students is based on their class participation (15% of the grade) and a take-home exercise on the topics learned during the course (85% of the grade). The exercise consists in replicating the examples considered during the class sessions using the WVS data of a different country than the one the professor uses in class to illustrate the application of the methods learned. The exercise can be completed along the semester and will be submitted at the end of the course.