•     Principles of counting; elements of combinatorics
•     Models of random dependent processes: probability ranges, probability measures
•     Conditional probabilities; independence; Bayesian rule
•     Random variables and their distributions; characteristics of the distributions: Expected value and variance
•     Discrete distributions: Laplace distribution; binomial distribution; geometric distribution
•     Approximation of the binomial distribution by the normal distribution;
•     Approximation of the binomial distribution by the Poisson distribution
•     Distributions with densities: Equal distribution; Normal distribution; Exponential distribution
•     Common distributions of several random variables: discrete and with densities; independence from random variables; conditional distributions; sums of independent random variables and their distributions
•     Characteristics of common distributions: Expected value, covariance and correlation; conditional expectation
•     Limit theorems: weak law of large numbers and relative frequencies; the central limit theorem
•     Data analysis and descriptive statistics: histograms; empirical distribution; characteristics of sample distributions; examples of misleading descriptive statistics; linear regression
•     Elementary terms and techniques of testing and estimation: maximum likelihood principle; confidence intervals; hypothesis tests; first and second type errors

E. Behrends: Elementary Stochastics, Springer, 2013
    H.-O. Georgii: Stochastics: Introduction to Probability Theory and Statistics, De Gruyter, 2007
    U. Krengel: Introduction to probability theory and statistics, Vieweg, 2005
    D. Meintrup, S. Schäffler, Stochastics: Theory and Applications, Springer, 2005.
    Most of the books listed below are available online at the UB. For this purpose, there is an extensive hand apparatus for stochastics in the mathematic library.