- Introduction to quantitative research methods:
- Use of primary data sources such as in survey research
- Use of secondary data sources such as patent data bases and financial data bases, bibliometrics, etc
- Use of modeling and simulation
- Quantitative research methodology:
- Underlying assumptions of quantitative analysis
- Design and implementation of quantitative studies
- Reading and reporting quantitative research
- Validity and reliability issues
- Statistical analysis:
- Statistical inference, association and causation among variables and multivariate techniques
- Statistical packages such as SPSS and AMOS
FME3518 Quantitative Research Methods in Industrial Economics and Management 7.5 credits
Course main content: This is a course in practical application of advanced quantitative methods for doctoral students. The course first introduces methods to collect and store data from existing databases, generate new data by survey approaches, and prepare data further analysis. Second, the course provides theoretical background to analyse data. Third, it focus established models to estimate data. Finally the students applies quantitative methods by replicating existing research from a large number of examples and prepare to presents their works as professional papers.
Information per course offering
Course offerings are missing for current or upcoming semesters.
Course syllabus as PDF
Please note: all information from the Course syllabus is available on this page in an accessible format.
Course syllabus FME3518 (Spring 2019–)Headings with content from the Course syllabus FME3518 (Spring 2019–) are denoted with an asterisk ( )
Content and learning outcomes
Course contents
Intended learning outcomes
- Describe the breadth of research approaches and data collection techniques available to a quantitative researcher in the field of Industrial economics and management
- Describe the basic ideas and underlying assumptions of quantitative analysis
- Describe basic elements of design and implementation of quantitative studies
- Understand how to read quantitative research in a critical way
- Understand how to report quantitative research in a publishable way
- Appreciate quality aspects in conclusions based on statistical reasoning
- Be familiar with basic statistical inference
- Be familiar with and able to test statistical association and causation among variables
- Be familiar with and able to use basic multivariate data analysis techniques
- Be familiar with the basics of widely used computer based statistical packages such as SPSS and AMOS
Literature and preparations
Specific prerequisites
Enrolled at doctoral program in Industrial management or equivalent
Recommended prerequisites
Enrolled at doctoral program in Industrial management or equivalent.
Literature
You can find information about course literature either in the course memo for the course offering or in the course room in Canvas.
Examination and completion
Grading scale
P, F
Examination
- TEN1 - Exam, 7.5 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.
If the course is discontinued, students may request to be examined during the following two academic years.
Other requirements for final grade
Mandatory to be present and participate in all modules
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
Education cycle
Third cycle