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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 2022-2023. Please note that changes may occur.

Facts
Course code

MSB104

Version

1

Credits (ECTS)

10

Semester tution start

Spring

Number of semesters

1

Exam semester

Spring

Language of instruction

English

Note

Course does not start before spring 2023

Content
The subject areas covered are:
  • The foundations of empirical research
  • How to design and structure empirical studies to address a real-world business challenge
  • How to go about collecting data in order to address the business challenge at hand
  • How to solve these challenges by utilizing 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:

  • Understand the academic writing and publishing process
  • Systematically and critically review an existing body of empirical literature
  • 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

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
Required prerequisite knowledge
None
Recommended prerequisites
Appropriate bachelor background in core business fields as well as mathematics for business/economic and statistics for business/economics.
Exam
Form of assessment Weight Duration Marks Aid
Group project 1/1 Letter grades

The course is assessed based on a student group project with a joint grade for all students in one group.

Coursework requirements
Group consultations with the supervisor
Students are required to attend all scheduled group consultations with the course supervisor for submitting their group work.
Course teacher(s)
Course coordinator: Dora Zsuzsanna Simon
Course teacher: Hongyan Shi
Method 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.

Open for
Master in Accounting and Auditing Business Administration - Master of Science
Course assessment
Students will have the opportunity to give feedback on the course in an early dialogue and a written course evaluation. 
Overlapping courses
Course Reduction (SP)
Research Methods for Business Sciences (MØA103) 10
Data Analytics and Research Methods (MØA112) 10
Data Analytics and Research Methods (MSB112) 10
() 20
() 20
() 30
() 30
Literature
Search for literature in Leganto