Learning objectives / competences:
Students are able to transfer business management questions into suitable experimental designs, to model and evaluate them using suitable software and to interpret the results in relation to the application. They work on problems independently in small groups using suitable software (R, Jamovi, SPSS) and briefly present their results. By attending this module, students recognise that an understanding of the quantitative aspects behind business management issues is necessary.
Contents:
Repetition of the concept of statistical tests
Double t-test, t-test for related samples, Kruskal-Wallis test
Dispersion decomposition, internal and external variance
Normal distribution, t-distribution, χ2-distribution, F-distribution and correlations between the distributions
Analysis of variance with one and several factors and interactions
Block schedules, repeated measures
Random and fixed effects
Multiple mean comparisons
Violation of model assumptions, in particular residual analysis
Applied methods of business administration:
Models and methods of analysis (research and analysis models):
Choice of appropriate experimental design
Quantitative-empirical methods (comparative - statistical, mathematical methods, data analyses):
Significance tests
Qualitative-interpretative methods (expert interviews, surveys, standardised surveys):
Interpretation of results
Teaching and learning methods:
Seminars