The course objective is training students on abstract thinking and acquiring basic knowledge in the field of probability, statistics and stochastic processes. The aim is for students to master the basic concepts of probability theory, to enable them to choose the appropriate statistical methods, to perform statistical analysis and to interpret the obtained results. The main goal is to enable students to apply theoretical knowledge from the theory of random processes in the field of telecommunications.

Student should use the acquired knowledge in further education. The student is qualified to make and solve mathematical models in the further education in professional subjects applying acquired knowledge from probability, statistics and stochastic processes.

Basic definitions in probability, conditional probability and Bayes’ formula. Random variable of discrete and continuous type, distribution functions. Two dimensional random variable. Conditional distribution. Numeric characteristics – expectation, dispersion, covariance, correlation. Conditional expectation. Limit theorems. Statistics – point estimate and interval estimate, parametric and nonparametric hypotheses and significance testing. Stochastic processes – general notions. Stochastic process transformation- derivative, integral. Poisson process, white noise, telegraph signal. Markov chains and processes, birth-death process, mass service systems. Stationary process. Mass service systems.

Lectures, Numerical calculation practice and computer practice (statistics). Consultations. Lectures are conducted combining theoretical part of the subject matter with characteristic examples which facilitate understanding. During practice classes, which accompany the lectures, some characteristic problem tasks are done and the presented material is discussed in more detail. In addition to the lecture and practice classes there are regular consultations.