CC 303: Quantitative Methods
Contents
In today's world, leading companies rarely make complex decisions based on gut feelings, but instead systematically collect and analyze data, and model important relationships. Based on the empirical insights, decisions are also made systematically – with the help of optimization as decision support. For many business analytics methods – whether descriptive, predictive or prescriptive – linear algebra is a fundamental building block that is discussed in this course. Further important topics include the modeling and solution of practical optimization problems, including spreadsheet-based tools.
Learning outcomes
Students are supposed to learn about the fundamental methods of linear algebra and apply them to typical problems in business administration. In addition, structured approaches and analytical skills should be trained, e.g. the modeling of real decision-making situations as a mathematical optimization problem and their solution with the help of algorithms.
After completing the lecture, students should have subject-specific knowledge and be able to apply it to analyze, model and solve managerial problems in the respective academic disciplines.
Necessary prerequisites
–
Recommended prerequisites
–
Forms of teaching and learning | Contact hours | Independent study time |
---|---|---|
Lecture | 2 SWS | 1 SWS |
Exercise class | 2 SWS | 1 SWS |
Tutorial | 2 SWS | 1 SWS |
ECTS credits | 3 |
Graded | yes |
Workload | 90h |
Language | German |
Form of assessment | Written exam (45 min), optional bonus exercises during the semester |
Restricted admission | no |
Further information | – |
Examiner Performing lecturer | ![]() | Prof. Dr. Cornelia Schön Prof. Dr. Cornelia Schön |
Frequency of offering | Fall semester |
Duration of module | 0.5 semesters |
Range of application | B.Sc. Bus. Adm. |
Preliminary course work | – |
Program-specific Competency Goals | CG 1, CG 2, CG 4 |
Literature | s. syllabus |
Course outline |
|