1) Introduction: defining qualitative and quantitative statistical variables, the usefulness of statistics, the notions of population, sample, individual, and survey.
2) The basics of descriptive statistics: defining the concepts of absolute and relative frequency, descriptive tables and graphs.
3) Statistics of position, dispersion, shape and concentration (Gini index)
4) Bivariate data analysis: distinguishing causality and correlation, statistical independence, marginal and conditional distributions, contingency tables, regression.
6) Introduction to probability theory: axiomatics, combinatorial analysis, conditional probability and independence, law of total probabilities and Bayes' theorem.
7) Discrete random variables, expectation and variance, parametric distributions, bivariate distributions.
