Facility & Real Estate Management PT
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Academic & Empirical Methods

level of course unit


Learning outcomes of course unit

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
• Independently analyze and structure data sets as well as present and critically evaluate information

prerequisites and co-requisites


course contents

• Principles of academia and academic work
o Science and academic language
o Literature research
o Citation and source work
o Avoidance of plagiarism
• Principles of data analysis
o Statistical characteristics and variables
o Univariate and multivariate description and exploration of data
o Correlation and regression analyses
o Basic programming knowledge for data preparation
o Analysis and presentation of information from data sets

The module contains 25% exercises. This form of teaching takes place in small groups.

recommended or required reading

• Heisen, M. R. and M. Theisen 2017. Wissenschaftliches Arbeiten: erfolgreich bei Bachelor- und Masterarbeit. Munich: Franz Vahlen
• Fahrmeir, L., R. Künstler, I. Pigeot, I. and G. Tutz, 2012. Statistics: Der Weg zur Datenanalyse. 7th edition. Berlin: Springer
• Fahrmeir, L., Kneib, T. & Lang, S., 2009. Regression: Modelle, Methoden und Anwendungen. 2nd edition. Berlin: Springer
• Hetland, M., 2005. Beginning Python From Novice to Professional. New York: Spring-er-Verlag
• Ernesti, J. and P. Kaiser, 2012. Python 3 - Das umfassende Handbuch. 3rd edition. Bonn: Galileo Computing
• Weitz, E. 2018. Konkrete Mathematik (nicht nur) für Informatiker. Mit vielen Grafiken und Algorithmen in Python. Wiesbaden: Springer

assessment methods and criteria

Term paper and written exam

language of instruction


number of ECTS credits allocated


eLearning quota in percent


course-hours-per-week (chw)


planned learning activities and teaching methods

Blended Learning

semester/trimester when the course unit is delivered


name of lecturer(s)

Director of Studies

year of study


recommended optional program components


course unit code


type of course unit

integrated lecture

mode of delivery


work placement(s)