Energy & Sustainability Management FT
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Scientific and Empirical Methods

level of course unit

Introduction

Learning outcomes of course unit

The students are able to:
• Describe and apply the fundamentals of academic work
• Research, evaluate and cite specialist literature
• Present and apply scientific methods of literature analysis
• Describe and apply concepts and methods of descriptive and explorative statistics

prerequisites and co-requisites

Blended Learning

course contents

Science and scientific methods
• Science and scientific language
• Literature research
• Citation and source work
• Avoidance of plagiarism

Data analysis:
• Statistical characteristics and variables
• Uni- and multivariate description and exploration of data
• Correlation and regression analysis
• Basic programming skills for data preparation
• Analysis and presentation of information from data sets

The module is made up of 25% exercises. This form of teaching takes place in small groups.

recommended or required reading

• Heisen, M. R. und M. Theisen, 2017. Wissenschaftliches Arbeiten: erfolgreich bei Bachelor- und Masterarbeit. München: Franz Vahlen
• Weiz, E., 2018. Konkrete Mathematik (nicht nur) für Informatiker. Mit vielen Grafiken und Algorithmen in Python. Wiesbaden: Springer
• 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
• Ross, S., M., Statistik für Ingenieure und Naturwissenschaftler. 3. Auflage. Spektrum Akademischer Verlag

assessment methods and criteria

Term paper and written exam

language of instruction

German

number of ECTS credits allocated

7

eLearning quota in percent

50

course-hours-per-week (chw)

3.5

planned learning activities and teaching methods

Blended Learning

semester/trimester when the course unit is delivered

1

name of lecturer(s)

Asc. Prof. (FH) Dipl.-Ing. Christian Huber

year of study

1

course unit code

WIS.1

type of course unit

integrated lecture

mode of delivery

Compulsory

work placement(s)

none