Quantitative Research Methods in Innovation Studies (DSV610)
This course is an entry-level course to quantitative analysis in innovation studies for PhD students. It features an introduction to the software R, discusses data reduction techniques, regression and correlation analyses, as well as social network analyses.
Course description for study year 2022-2023
Semester tution start
Number of semesters
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Students will have a basic overview of quantitative analysis techniques and their application in innovation research.
Students will be able to evaluate the use of methods and the main data sources relevant for innovation research.
Students will be able to develop new knowledge and new theories on innovation using quantitative methods.
Students will be able to conduct innovation research at a basic level using quantitative methods, including factor analysis, regression and correlation analysis, and social network analysis.
Students will be able to formulate new research questions and conduct innovation research using quantitative methods.
Students will be able to handle the statistical software R
Students will be able to assess when and how to use quantitative research methods.
Students will be able to discuss academic analyses in the field at a basic level.
Students will be able to assess research using quantitative methods.
Required prerequisite knowledge
|Form of assessment||Weight||Duration||Marks||Aid|
|Term paper||1/1||Passed / Not Passed|
To obtain 5 ECTS point requires active participation during the course as well as an accepted paper of 3.000-4.000 words demonstrating competence in using quantitative methods. The paper should be based on the topic of the PhD thesis and reflect literature used in the course. If quantitative methods will not be used in the thesis a paper answering given tasks could substitute a normal paper. However, the concrete form of the written delivery can be further discussed during the course.Term paper - appr. 3.000-4.000 words. The paper will be assessed as a pass/fail.