At the end of the course, students will be able to:

• select suitable statistical procedures to answer given content-related questions,
• interpret statistical ratios and graphs and produce them themselves in a suitable manner,
• justify the relevance and necessity of statistical information processing in the context of the scientific and social process,
• name basic concepts and procedures of descriptive statistics,
• competently apply basic descriptive-statistical procedures, taking into account the characteristics of the data,
• identify limitations in the significance of descriptive data analyses and their results, taking into account content-related questions

none

• Probability distributions: Binomial distribution, normal distribution
• Concept of probability, calculating with probabilities
• Lorenz curve and Gini coefficient, concentration and ratio index numbers, indices
• Bivariate descriptive-statistical procedures: Correlation and regression analysis, contingency analysis (incl. Chi2 test)
• Univariate descriptive-statistical methods: Frequencies and frequency distributions, graphical representation of data, measures of location and dispersion.
• Basic concepts of descriptive statistics: characteristic values, measurability, scale levels, etc.

Dürr, W., & Mayer, H. (1992): Wahrscheinlichkeitsrechnung und Schließende Statistik. München/Wien: Carl Hanser Verlag.
Field, A. (2018). Discovering statistics using IBM SPSS statistics (5th edition). London: Sage Publications Ltd.
Kockelkorn, U. (2012). Statistik für Anwender. Berlin/Heidelberg: Springer.
Mayer, H. (2006): Beschreibende Statistik (4. Aufl.). München/Wien: Hanser Verlag.
Quatember, A. (2005): Statistik ohne Angst vor Formeln. Ein Lehrbuch für Wirtschafts- und Sozialwissenschaftler. München: Pearson Studium.
Rasch, B., Friese, M., Hofmann, W., & Naumann, E. (2014a). Quantitative Methoden 1. Einführung in die Statistik für Psychologen und Sozialwissenschaftler. Berlin: Springer.
Rasch, B., Friese, M., Hofmann, W., & Naumann, E. (2014b). Quantitative Methoden 2. Einführung in die Statistik für Psychologen und Sozialwissenschaftler. Berlin: Springer.
Wewel, M.C. (2010). Statistik im Bachelor-Studium der BWL und VWL. München: Pearson Studium.

Moderated group work, lecture, working on exercise examples

Cumulative module examination
The module grade is calculated weighted by the ECTS credits of the individual courses of the module and results as follows:
ILV "Statistics I" - 3 ECTS Credit

• Assessment type: Continuous assessment
• Assessment method/s: exercise sheets, presentation of exercises, written final examination