Introduction to Quantitative Methods - SIMM16
7,5 CREDITS | SPRING TERM
This course is an introductory course in quantitative methods at Master's level. The course will also be open to staff at the faculty who want to improve their knowledge in this area, e.g. in order to be able to teach quantitative methods courses or supervise students using quantitative methods in their thesis.
Basic concepts in quantitative methods
The aim of this course is for students with little prior knowledge of quantitative methods to develop an understanding of the basic concepts and fundamental principles guiding the use of quantitative methods, acquire basic practical skills with regard to the performance of statistical analysis and develop the ability to critically assess quantitative research. The participants formulate a research question that includes a hypothesized causal relationship and that can be addressed using an available dataset. During the course different techniques for processing and analyzing data will be introduced and the participants will, mainly under teacher supervision, work on answering their own research question using the tools presented to them in the lectures. Participants will also learn to assimilate and evaluate existing quantitative social science research as it is presented in scientific journals and/or reports.
The course will focus on
- performing basic statistical analysis (of secondary data, using SPSS) and
- comprehending and evaluating scientific papers based on quantitative methods (with focus on the participants own areas of research).
The course will be given in English. It does not presume any previous knowledge of statistics.
Online course platform
This course uses Canvas as the online course platform. The course platform will be opened one week 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.
Excerpt from student evaluation
"One of the most satisfacctory aspects of the course was learning skills I never thought I'd be able to master. I've always hated math and frankly everything that deals with numbers, and wanted to
challenge myself by taking this particular course.
I'm proud of myself for making this decision and doing my best throughout the course. I also liked how much freedom we students had in choosing our research questions and topics. The teachers were careful not to push us e.g. towards research problems in their respective personal areas of interest."