1. Introduction to probability (concept of probability, computing probabilities, conditional probability, Bayes¿ Theorem).
2. Introduction to random variables (probability, density and distribution functions, characteristics of a random variable, transformations).
3. Probability models (Binomial, Poisson, Exponential, Normal).
4. Random vectors (probability, density and distribution functions in two dimensions, transformations of random vectors).
5. Stochastic processes (concept, classification, stationarity, ergodicity).