Academic & Empirical Methods
Niveau
Introduction
Learning outcomes of the courses/module
The students are able to:
• Describe and apply the fundamentals of academic work
• Research, evaluate and quote specialist literature
• Present and apply academic methods of literature analysis
• Understand and apply concepts and methods of descriptive and explorative statistics
• Describe and apply the fundamentals of academic work
• Research, evaluate and quote specialist literature
• Present and apply academic methods of literature analysis
• Understand and apply concepts and methods of descriptive and explorative statistics
Prerequisites for the course
none
Course content
• Principles of academic and scientific work
o Science and scientific language
o Literature research
o Citation and source work
o Avoidance of plagiarism
• Principles of descriptive and explorative statistics
o statistical characteristics and variables
o univariate and multivariate descriptive and explorative statistics
o index numbers
o correlation and regression analyses
o concentration measurement
o time series analysis
o Science and scientific language
o Literature research
o Citation and source work
o Avoidance of plagiarism
• Principles of descriptive and explorative statistics
o statistical characteristics and variables
o univariate and multivariate descriptive and explorative statistics
o index numbers
o correlation and regression analyses
o concentration measurement
o time series analysis
Recommended specialist literature
• Heisen, M. R. und M. Theisen 2021. Wissenschaftliches Arbeiten: erfolgreich bei Bachelor- und Masterarbeit. München: Franz Vahlen
• Bourier, G., 2018. Beschreibende Statistik: Praxisorientierte Einführung – Mit Aufgaben und Lösungen. 13. Auflage. Wiesbaden: Springer Gabler
• Fahrmeir, L., R. Künstler, I. Pigeot, I. und G. Tutz, 2012. Statistik: Der Weg zur Datenanalyse. 7. Auflage. Berlin: Springer
• Fahrmeir, L., Kneib, T. & Lang, S., 2009. Regression: Modelle, Methoden und Anwendungen. 2. Auflage. Berlin: Springer
• Bourier, G., 2018. Beschreibende Statistik: Praxisorientierte Einführung – Mit Aufgaben und Lösungen. 13. Auflage. Wiesbaden: Springer Gabler
• Fahrmeir, L., R. Künstler, I. Pigeot, I. und G. Tutz, 2012. Statistik: Der Weg zur Datenanalyse. 7. Auflage. Berlin: Springer
• Fahrmeir, L., Kneib, T. & Lang, S., 2009. Regression: Modelle, Methoden und Anwendungen. 2. Auflage. Berlin: Springer
Assessment methods and criteria
Term paper and written exam
Language
German
Number of ECTS credits awarded
6
Share of e-learning in %
50
Semester hours per week
3.0
Planned teaching and learning method
Blended Learning
Semester/trimester in which the course/module is offered
1
Name of lecturer
Director of Studies
Academic year
1
Key figure of the course/module
WIS.1
Type of course/module
integrated lecture
Type of course
Compulsory
Internship(s)
none