Research Methods (S)

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. More information Students are made familiar with the opportunities that are offered by multivariate econometric analysis of real world economic data. The focus is on the contribution of this methodology to strategic management. Upon completion of this course, the student can: understand the possibilities of applications, conditions of usage 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) construct and estimate a regression model him/herself and report about the results (5.a, 8.d, 11.g)