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Quantitative Data Analysis in R - SIMM61


The aim of this course is for the student to develop an understanding of key concepts and principles guiding the use of quantitative methods, relate the use of quantitative methods to social science theory building and assessment, acquire practical skills with regard to the performance of statistical analysis and visualisation in R, and develop the ability to independently and critically assess quantitative research.


Course content

The student formulates a research question that includes a hypothesised relationship in relation to social scientific theories on a particular theme, and that can be addressed using an available dataset. During the course different techniques for processing, visualising and analysing data in R will be introduced and the student works on answering their own research question using the tools presented to them in the lectures, seminars and computer labs. The student also learns to assimilate and evaluate existing quantitative social science research as it is presented in scientific journals and/or reports.

Moreover, some of the multivariate statistical techniques most commonly used within the social sciences are presented and practiced in R. The focus lies on the relationship between research questions and different multivariate statistical techniques. The teaching includes theory and practice in analytical methods.

Online course platform

This course uses Canvas as the online course platform. The course platform will be opened two weeks before the course begins to all students who were accepted. Here you will be able to access literature, assignments, announcements, as well as participate in discussions and communicate with teachers. 


The course schedule can be found under the course information on the right. Please note that the final version of the schedule will be made available four weeks before the course begins, and changes may occur until that point. A more detailed schedule will be available on the course platform on Canvas.

About the course

Next course period:
2024-11-01 to 2025-01-19

Course schedule:
List view | Calendar view

Course syllabus

Course literature