Research Methods (MSB104)
Solving complex tasks and presenting them in a scientific manner is the core of modern business analytics. Solving such tasks requires training, which is at the heart of this course. The course builds on the Data Analytics course and brings its content to a practical application. It is challenged-based and improves the students’ abilities in scientific writing and group work.
Course description for study year 2023-2024. Please note that changes may occur.
Course code
MSB104
Version
1
Credits (ECTS)
10
Semester tution start
Spring
Number of semesters
1
Exam semester
Spring
Language of instruction
English
Content
The subject areas covered are:
- The foundations of empirical research
- How to design and structure empirical studies to address a real-world empirical question
- How to go about collecting data in order to address the empirical question at hand
- How to solve the question using empirical data and advanced empirical tools
- How to convincingly present empirical insights
Learning outcome
Knowledge
On completion of the course, students will be able to:
- Systematically and critically review an existing body of empirical literature 1
- Formulate relevant research questions
- Develop an appropriate empirical research design
- Collect and analyse quantitative data
- Conduct high-level empirical analysis and adequately present their results
- Be familiar with ethical perspectives in empirical research and critically evaluate own data management practices
Skills
Students will be able to:
- Digest and evaluate scientific research
- Use data analytics in empirical problems
- Conduct an empirical study of high scientific quality
- Develop and critically assess research hypotheses and questions
- Demonstrate abilities to scientifically communicate in writing and presentation
Required prerequisite knowledge
Recommended prerequisites
Exam
Form of assessment | Weight | Duration | Marks | Aid |
---|---|---|---|---|
Folder evaluation | 1/1 | Letter grades |
The evaluation may be based on problem sets, group work, individual work.It is not possible to resit the exam.
Coursework requirements
Course teacher(s)
Course teacher:
Jon-Sander AmlandCourse coordinator:
Dora Zsuzsanna SimonCourse teacher:
Hammad ShaikhCourse teacher:
Kwadwo Atta-OwusuCourse teacher:
Hongyan ShiCourse teacher:
Peter MolnarStudy Program Director:
Yuko OnozakaMethod of work
In this course, you will learn through group work, individual study and consultation with the course supervisor.
Expectations: 280 ECTS hours divided between lectures, meetings, independent study, and out-of-class (group) work.
Overlapping courses
Course | Reduction (SP) |
---|---|
Research Methods for Business Sciences (MØA103_1) | 10 |
Data Analytics and Research Methods (MØA112_1) | 10 |
Data Analytics and Research Methods (MSB112_1) | 10 |
Research Methods for Business Sciences, Data Analytics and Research Methods ( MØA103_1 MØA112_1 ) | 20 |
Data Analytics and Research Methods, Research Methods for Business Sciences ( MSB112_1 MØA103_1 ) | 20 |
Data Analytics and Research Methods, Data Analytics and Research Methods ( MSB112_1 MØA112_1 ) | 30 |
Data Analytics and Research Methods, Research Methods for Business Sciences, Data Analytics and Research Methods ( MSB112_1 MØA103_1 MØA112_1 ) | 30 |