The course provides an overview of modern quantitative research methods, with particular focus on applications in studies of entrepreneurship and innovation.
Information for research students about course offerings
Link to course homepage and application:
Advanced quantitative methods in entrepreneurship and innovation research - SSES
Course start: Autumn 2023
6th of September 08:00-12:00 online
21-22nd of September at SSES
6th of October 10:00-12:00 online
20th of October 10:00-12:00 online
26th of October 10:00-15:00 online
27th of October 10:00-15:00 online
Deadline to apply 13th of August 2023
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Content and learning outcomes
The course provides an overview of quantitative research methods, with particular focus on applications in studies of entrepreneurship and innovation. Basic understanding of quantitative methods, including training in statistics and propability theory, are expected prerequisites. Participants are given an opportunity to broaden and deepen their understanding of what tools that are available for common research problems, with emphasis on specification, estimation, interpretation and valuation of various forms of mathematically formulated models. The overall ambition is for course participants to gain useful overview of how data can be analysed using economtric models and machine learning tools, with emphasis on methods that are used in contemporary state-of-the-art research on entrepreneurship and innovation.
The central sections of the course are constituted by presentations and exercises introducing important concepts and techniques. Prioritization of what techniques that are treated at greater depth is to some extent determined by participants’ interests and needs.
Intended learning outcomes
After having completed the course, participants should have abilities to
- identify appropriate quantitative methods in adressing different types of research questions, and assess their applicability
- orient themselves within the realm of contemporary quantitative research methodology
- assess methodological choices in contemporary quantitative research on entrepreneurship and innovation
Literature and preparations
Admitted doctoral student.
Completed course in Statistics, Probability Theory and Quantitative Method of at least 12 ECTS, of which 5 credits should be at postgraduate level.
Examination and completion
If the course is discontinued, students may request to be examined during the following two academic years.
- INL1 - Assignment, 3.5 credits, grading scale: P, F
- SEM1 - Seminars, 1.5 credits, grading scale: P, F
Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.
The examiner may apply another examination format when re-examining individual students.
Opportunity to complete the requirements via supplementary examination
Opportunity to raise an approved grade via renewed examination
- All members of a group are responsible for the group's work.
- In any assessment, every student shall honestly disclose any help received and sources used.
- In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.
Further information about the course can be found on the Course web at the link below. Information on the Course web will later be moved to this site.Course web FME3547