MSc International Relations and Diplomacy students.
This course explores various statistical methods as applied to international relations and comparative politics. It starts with simple, but essential, descriptive statistics. It further introduces learners to the topics of inferential statistics and, notably, linear and logistic regressions. The course finishes with the cutting-edge methods related to experiments in social science.
By the end of this course, the learners will be able to
identify data relevant for various research questions related to international relations or comparative politics;
describe and analyse the data with modern quantitative research methods techniques;
interpret the results of quantitative analysis;
evaluate and critique a research design; and
distinguish between the concept of causality and correlation.
On the right-hand side of the programme front page of the E-Prospectus you will find a link to the online timetables.
Mode of instruction
This course is a mix of lectures and tutorials. Tutorials serve to put theory into practice and get a good command of statistical software.
Study load: 140 hours
Final grades are calculated based on four components:
On-line test (20%),
In-class challenge (10%),
Written assignment I (30%),
Written assignment II (40%),
Details for submitting papers (deadlines) are posted on Brightspace.
You can find more information about assessments and the timetable exams on the website.
Failed partial grades or components should be compensated by passed partial grades or components. The calculated grade must be at least 5,5 to pass the course. It is not possible to re-sit a partial grade or component once you have passed the course.
Partial grades will remain valid for one academic year.
Should a student fail the overall course, s/he can complete the course in the second year of the programme.
Diez, David, Christopher Barr and Mine Cetinkaya-Rundel (2015). OpenIntro Statistics. Third Edition. Available under a Creative Commons license. Visit the website of OpenIntro for a free PDF, to download the textbook's source files, or for more information about the license.
Academic articles announced before the lectures.
Students register via USIS based on the programmes group division. Use Brightspace for course information.
Dr. J.J. Kantorowicz email@example.com
A. Pourebrahimi Andouhjerdi firstname.lastname@example.org