LFU:online

The students

• describe selected methods for data collection, data processing and data evaluation, taking data protection into account;

• use data management in selected statistical and database programs;

• apply selected relevant statistical data collection and analysis techniques as well as corresponding calculations

• select adequate graphic display options

• present the results accordingly

• interpret their expressiveness

• select the correct method and display type for the respective scientific study.

• Methods for data collection, data processing, data evaluation, consideration of data protection

• Basics of selected statistics and database programs, e.g. SPSS, MS Office, CITAVI

• Data entry and evaluation, e.g. in MS Excel

• Basics of descriptive and inductive statistics

• Variables and their characteristics, scale levels;

• Graphical and algebraic methods for describing a feature, e.g. histogram, frequency functions, cumulative distribution function, measures of position and dispersion, box plots, methods for analyzing two or more features, selected statistical data collection and analysis techniques: evaluation, interpretation and presentation of data

Lecture, exercises/practical application

Practical task

Bühl, Achim. SPSS. Einführung in die moderne Datenanalyse. 16. aktualisierte Auflage, Pearson Studium, München (2018)

Hug, Theo/Poscheschnik, Gerald. Empirisch Forschen. Die Planung und Umsetzung von Projekten im Studium. 3. Auflage, UVK, Konstanz (2020)

Completion of an introductory course in scientific work