Themen der Lehrveranstaltung
- Descriptive statistics: basic definitions, classification of variables, overview of sampling techniques, frequency distributions, graphical representations, measures of central tendency and variability.
- Probability: introduction to probability, basic axioms, conditional probability, independence, Bayes' theorem, introduction to discrete and continuous random variables, expected values and variance, introduction to known distributions for discrete and continuous random variables, central limit theorem.
- Inference: Sample statistics and sample distributions, introduction to estimators and their properties, point estimation, interval estimation (mean, proportion, difference between means, paired samples), hypothesis testing (mean, proportion, difference between means, paired samples)
- Additional topics: analysis of bivariate dependencies between variables using correlation and regression, introduction to R software for descriptive analysis, statistical inference and regression.
Unterrichtsform
Lectures and exercises.