Research Methods

Description

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.b         Based on the critical analysis of various quantitative and qualitative research methods, makes an informed choice about a relevant research method to solve a (business) economics problem relevant to practice. 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.d         Assesses the impact on reliability and validity of the results when developing the research design. 6.e         From qualitative and quantitative research findings, draws scientific conclusions that bear practical relevance. 8.c         Identifies the limitations of research and questions the research findings. 8.d         Sets forth a logical and coherent argumentation to support choices made when solving a (business) economic problem with practical relevance. 8.e         Ensures the relevance, precision and scientific character of his own work and takes into account possible feedback. 11.g       Is familiar with relevant ICT applications and uses the knowledge and skills to solve (business) economic problems. ERS learning outcomes Students will be able to document and communicate their methodology clearly and comprehensively, ensuring that their regression analyses can be reproduced and validated by others in the academic community. Students will be able to identify potential biases in their regression models (e.g., omitted variable bias, selection bias) and take steps to mitigate them to ensure fair and equitable results. Explanation Students are introduced to the possibilities offered by multivariate econometric analysis of real economic data. The focus is on clarifying the contribution of this methodology to the development of strategic policies. Upon completion of the course unit, the student will be able to: -understand the applicability, conditions of use and limitations of linear regression (5.b, 5.c, 6.b, 6.c, 6.d) -interpret and evaluate the output of an estimated regression model (6.e, 8.c, 8e) -construct, estimate and report on the results of a regression model  (5.a, 8.d, 8e, 11.g) In addition, the course aims to provide students with insights into qualitative and quantitative research methods. We will briefly zoom in on various paradigms and research philosophies that underlie and guide research. Furthermore, special attention will be paid to the choice between qualitative and quantitative research methods, the tension that exists between them but also the opportunities offered by combining both approaches. (6.b, 6.c, 6.d, 6.e)