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751-0441-00L 2 Credits BSC D-USYS
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Scientific Analysis and Presentation of Data

Lecturers & Examiners: Prof. Dr. Hubert Pausch, Dr. Naveen Kumar Kadri, Dr. Alexander Leonard
VVZ CR n/a

Last Updated: 2026-02-05 16:14:40

Abstract

Students will get an introduction to the scientific work with data covering all steps from data import from Excel via statistical analyses to producing correct scientific graphical output. Exercises with the software R/RStudio will provide hands-on opportunities to get acquainted with data analysis and presentation in adequate graphs.

Objective

This lecture with exercises gives an introduction to the scientific work with data, starting with data acquisition and ending with statistical analyses as they are often required for a bachelor thesis (descriptive statistics, linear regression, simple analyses of variance etc.). Using open-source R/RStudio software will be the primary focus via a hands-on approach. An imporant aspect will be to learn which graphical representation of data are best suited for the task (how can data be presented clearly and still scientifically correct?)

Content

Tentative Programme: - Introduction - Introduction to 'R' - Data import and graphical presentation - Correct and problematic graphical data displays - Statistical distribution and confidence intervals - Statistical tests - Repetition and hands-on applications - Correlation analysis - Linear regressions - Analysis of Variance Last week of semester: examination (Leistungskontrolle)

Resources

Lecture Notes

German and English

General Information

Language
English
Levels
BSC
Frequency
Yearly recurring

Examination

Type
end-of-semester examination
Mode
written 90 minutes
Aids
None
Schriftliche Prüfung (ohne Benützung der Kursunterlagen). Es werden inhaltliche Fragen gestellt zu ausgewählten Aspekten aus dem Kurs, zur Interpretation der im Kurs bearbeiteten und besprochenen Daten, zu generellen Aspekten der grafischen Darstellung von Daten und zu einfacheren R-Befehlen zur Kontrolle der grundsätzlichen Fähigkeit der Studierenden, mit der Kurssoftware arbeiten zu können.

Course Components

Type Title Time & Place Hours
lecture with exercise Scientific Analysis and Presentation of Data
  • Wed 08:15-10:00 (HG E 19)
2 h weekly

Offered In