Applied Data Analysis (ILV)

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Course lecturer:

FH-Prof. Dr.

 Christoph Ungermanns

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Specialization AreaAutomisation
Course numberB2.05271.40.320
Course codeADA
Curriculum2018
Semester of degree program Semester 4
Mode of delivery Presencecourse
Units per week2,0
ECTS credits2,5
Language of instruction German

The students have basic knowledge in applied data analysis. They know the main statistical measures of central tendency and dispersion of a dataset as well as their interpretation. They can visualize the data graphically in different ways and describe characteristic features. Furthermore, they are able to apply the Gaussian and Student t-distributions and make statements about confidence intervals and significances.

Measures of central tendency and dispersion, graphical methods: histogram, scatter plot, cumulative frequency, probability plot, covariance, correlation, Gaussian distribution, student-t distribution, confidence interval, significance

W. Polasek, EDA Explorative Datenanalyse, Springer Verlag
J. Schwarze, Grundlagen der Statistik I: Beschreibende Verfahren, NWB Verlag
R. Kosfeld Statistik: Grundlagen - Methoden - Beispiele, Springer Verlag

Lecture with integrated exercises