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Mathematics


Module name (EN):
Name of module in study programme. It should be precise and clear.
Mathematics
Degree programme:
Study Programme with validity of corresponding study regulations containing this module.
Business Psychology, Bachelor, regulation 01.10.2026
Module code: BWP-105
SAP-Submodule-No.:
The exam administration creates a SAP-Submodule-No for every exam type in every module. The SAP-Submodule-No is equal for the same module in different study programs.
P470-0005
Hours per semester week / Teaching method:
The count of hours per week is a combination of lecture (V for German Vorlesung), exercise (U for Übung), practice (P) oder project (PA). For example a course of the form 2V+2U has 2 hours of lecture and 2 hours of exercise per week.
2V+2U (4 hours per week)
ECTS credits:
European Credit Transfer System. Points for successful completion of a course. Each ECTS point represents a workload of 30 hours.
5
Semester: 1
Mandatory course: yes
Language of instruction:
German
Assessment:
Written exam

[updated 09.11.2026]
Applicability / Curricular relevance:
All study programs (with year of the version of study regulations) containing the course.

BWP-105 (P470-0005) Business Psychology, Bachelor, regulation 01.10.2026 , semester 1, mandatory course
Workload:
Workload of student for successfully completing the course. Each ECTS credit represents 30 working hours. These are the combined effort of face-to-face time, post-processing the subject of the lecture, exercises and preparation for the exam.

The total workload is distributed on the semester (01.04.-30.09. during the summer term, 01.10.-31.03. during the winter term).
60 class hours (= 45 clock hours) over a 15-week period.
The total student study time is 150 hours (equivalent to 5 ECTS credits).
There are therefore 105 hours available for class preparation and follow-up work and exam preparation.
Recommended prerequisites (modules):
None.
Recommended as prerequisite for:
Module coordinator:
Prof. Dr. Susan Pulham
Lecturer:
Adrienne Alt


[updated 18.09.2026]
Learning outcomes:
After successfully completing this module, students will be able to:
 
- describe economic relationships using functions of a single variable, to differentiate and integrate them in order to derive economically relevant quantities such as marginal costs and elasticities, and to solve optimization problems such as profit maximization,
- formulate systems of linear equations based on economic problems and systematically solve them using Gauss´s method,
- apply matrix calculus to economic and behavioral issues, such as using transition matrices to model and interpret consumer and customer behavior,
- model economic planning problems as linear optimization problems, solve them graphically, as well as using the Excel Solver, and evaluate and interpret the results for business decision-making using sensitivity analyses,
- apply financial models of interest, annuity calculations, and principal repayment to real-world financial problems and use them to make well-informed decisions,
- apply the quantitative methods they have learned independently and purposefully in order to analyze economic and psychological decision-making processes, and to build on this foundation in subsequent modules (e.g., statistics).

[updated 09.11.2026]
Module content:
Differential and integral calculus
- The concept of a function and elementary types of functions
- Functions of a single variable and differentiation rules
- Principles of integral calculus
- Economic applications (e.g., marginal costs, elasticities, and profit maximization)
 
Basics of linear algebra:
- Calculations with matrices
- Creating linear systems of equations
- Solving systems of linear equations using Gauss´s method
- Applications of matrix algebra in economics (e.g., transition matrices for modeling consumer and customer behavior)
 
Linear programming:
- Modeling economic planning problems as linear optimization problems
- Solving linear optimization problems graphically
- Solving a linear optimization problem using Excel Solver
- Conducting and interpreting a sensitivity analysis
 
Financial mathematics:
- Interest-rate models
- Annuity calculation
- Sinking fund calculation

[updated 09.11.2026]
Recommended or required reading:
- Arrenberg: Wirtschaftsmathematik für Bachelor. Mit Aufgaben und Lösungen, 5. überarbeitete Auflage, UVK-Verlag, München, 2019
- Domschke, Drexl: Einführung in Operations Research, 9. über. und verb. Auflage, Springer Gabler, Berlin, Heidelberg, 2015
- Domschke, Drexl, Klein, Scholl, Voß: Übungen und Fallbeispiele zum Operations Research, 8. aktualisierte u. verb. Auflage, Springer Gabler, Berlin, Heidelberg, 2015
- Luderer: Klassische Finanzmathematik: Grundideen, zentrale Formeln und Begriffe im Überblick, 1. Auflage, Springer Spektrum, Wiesbaden, 2019
- Tietze: Einführung in die angewandte Wirtschaftsmathematik: Das praxisnahe Lehrbuch - inklusive Brückenkurs für Einsteiger, 18. Auflage, Springer Spektrum, Berlin, Heidelberg, 2019
- Tietze: Übungsbuch zur angewandten Wirtschaftsmathematik: Aufgaben, Testklausuren und ausführliche Lösungen, 9. überarb. u. erw. Auflage, Springer Spektrum, Wiesbaden, 2014
- Tietze, Übungsbuch zur Finanzmathematik: Aufgaben, Testklausuren und ausführliche Lösungen, 8. verbesserte Auflage, Springer Spektrum, Wiesbaden, 2015

[updated 09.11.2026]
 
[Sun Nov 15 00:34:35 CET 2026, CKEY=bw1bwp, BKEY=wpsy, CID=BWP-105, LANGUAGE=en, DATE=15.11.2026]