Aims

This course evaluates the following learning outcomes:

The student

5.a        Uses static and dynamic models, graphically and algebraically, to analyse and solve (business) economic problems.
5.b        Uses descriptive and inferential statistical methods and techniques to solve (business) economic problems.
5.c        Studies and interprets associations between variables using linear regression techniques.

6.c        In line with the given practical relevance and the definition of the (business) economics problem, chooses and uses the appropriate techniques to acquire, analyse and interpret data.
6.e        From qualitative and quantitative research findings, draws scientific conclusions that bear practical relevance.

More information

Upon completion of this course, the student can:

• select and execute adequate research methods to solve statistical problems. (6.c)
• interpret the output of statistical computations that have been generated (5.a, 5.b, 6.e)
• check the underlying assumputions of methods used (5.a, 5.b)

Previous knowledge

The following preknowledge is required for this course:

• an in-depth knowledge of descriptive statistics for qualitative and quantitative data
• a thorough theoretical and practical understanding of probabilistic problems and hypothesis testing
• a theoretical and practical understanding of multiple linear regression models
• a basic understanding of time series methods

Is included in these courses of study

• Courses for Exchange Students Faculty of Economics and Business (Antwerp)
• Preparatory Programme: Master of Business Administration (Programme for students started in 2023-2024 or later) (Antwerp) 75 ects.