In terms of the so-called Assurance of Learning standards, this course pursues the following learning objectives:
* Knowledge acquisition: students will acquire knowledge of statistical methods and econometric models that are relevant when dealing with limited or nonmetric dependent variables.
* Knowledge application and judgement: in four assignments, students will learn to use and extend their knowledge on the basis of realistic cases and datasets.
* Research skills: the acquired knowledge involves (the application of) econometric techniques and thus directly contributes to students’ research skills.
* Communication and professional attitude: to realize the above learning objectives, interaction, feedback, and teamwork will be key. As a result, students will also sharpen their communication skills and improve their professional attitude.

Dependent variables rarely cover the full line of real numbers. Although the assumption of an unconstrained continuous dependent variable may be relatively harmless in quite some cases, many situations require a different approach. For example, when a consumer purchases packaged goods, he or she only buys an integer, nonnegative number of units. In surveys, Likert or semantic scales not only discretize but also limit a person’s true response, in that they impose minimum and maximum values. Finally, 0/1 phenomena by definition demand techniques that recognize the binary, nominal nature of the data. Ignoring the true characteristics of your data may lead to inefficient and inconsistent estimates and may generate nonsensical predictions. This skills training therefore introduces students to:
* different types of limited and/or nonmetric dependent variables and the inherent dangers of ignoring the data’s real nature;
* models that take into account the peculiarities of the data; and
* a particularly popular estimation technique that is flexible enough to estimate all studied models, namely Maximum Likelihood Estimation (MLE).
On the basis of structured assignments with realistic data, we will conduct econometric analyses in the open-source programming environment R.

Selected chapters from textbooks, course slides, course book

This course is in transition for the master Business Research.
See the Master Education and Examination Regulations for more information.

The following rule applies to master Business Research students who started the programme prior to academic year 2024-2025.
TRANSITIONAL REGULATION (EBS4001):
The master Business Research has been discontinued.
Courses of the Business Research master’s programme will continue to be offered until and including academic year 2025-2026 with exam opportunities running until and including 2026-2027.


PREREQUISITES:
* Experience with a statistical package like SPSS
* First experience with R (if not, preparatory assignment will be provided)
* Knowledge of multiple regression analysis and Ordinary Least Squares
* Knowledge of elementary and matrix algebra (if not, preparatory assignment will be provided)
* Knowledge of basic calculus