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FME3547 Advanced Quantitative Methods in Entrepreneurship and Innovation Research 5.0 credits

The course provides an overview of modern quantitative research methods, with particular focus on applications in studies of entrepreneurship and innovation.

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Application

For course offering

Autumn 2023 Start 28 Aug 2023 programme students

Application code

50269

Headings with content from the Course syllabus FME3547 (Autumn 2022–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

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

Specific prerequisites

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.

Recommended prerequisites

No information inserted

Equipment

No information inserted

Literature

No information inserted

Examination and completion

If the course is discontinued, students may request to be examined during the following two academic years.

Grading scale

P, F

Examination

  • 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

No information inserted

Opportunity to raise an approved grade via renewed examination

No information inserted

Examiner

Ethical approach

  • 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

Course room in Canvas

Registered students find further information about the implementation of the course in the course room in Canvas. A link to the course room can be found under the tab Studies in the Personal menu at the start of the course.

Offered by

Main field of study

This course does not belong to any Main field of study.

Education cycle

Third cycle

Add-on studies

No information inserted

Postgraduate course

Postgraduate courses at ITM/Industrial Economics and Management