[MACHINE TRANSLATION]

1 Introduction and motivation

2 Basic concepts of descriptive and exploratory analysis

3 Levels of measurement

4 Data distribution, measures of centrality, variability

5 Categorical data, frequency distribution

6 Classification of statistical units and description of relationships between variables

7 Graphical representation of data distribution and empirical relationships

8 Probability, conditional probability

9 Basics of inferential reasoning (population selection, point and interval estimation, goodness-of-fit tests)

10 Data transformation and standardisation

11 Direct data standardisation, contingency table weighting and interpretation

12 How to unravel relationships between traits and interpret results: interaction (moderation) and logic of elaboration

[END MACHINE TRANSLATION]