Mathematical and Empirical Methods, Forecasting
Component code / course code: UF-21.1
Semester: winter / summer
ECTS credits: 3
Lecture hours per week (SWS): 2
Lecturer: Prof. Dr. Winter
Language: German / English
Prerequisites:
Basics of statistics, such as those developed in the course on business statistics.
Qualification objectives:
After completing the course, students are able to describe and explain different methods for empirical research, apply methods to solve concrete problems in case studies with the help of a PC, analyse the suitability of certain methods for
selected problems and critically evaluate and appreciate corresponding analyses
Course contents:
- Inductive statistics and test procedures:
Sampling methods, estimation methods, test methods - Multiple regression models:
Bivariate non-linear regression, multiple regression, time series analysis - Forecasting:
State models, recurrent models, autoregressive models
Teaching format (e.g. online/in person lecture/Seminar/Lab etc.): Inverted classroom with corresponding self-study, learning workshop and plenary session
Examination type: written exam
