Applied Statistics

Basic concepts of probability: combinatorics (permutations, combinations, variations), random variables (discrete, continuous) and their distributions (Gauss, Poisson, Weibull, …), numerical characteristics (expected value, variance). 

Statistics: statistic design (definition of statistical hypothesis, sampling plans), data presentation, estimation of parameters (definition and properties of estimators), hypothesis testing (type one and type two error, power of test), confidence intervals, tests  (parametric, non-parametric, P-value, statistical significance), regression and correlation (linear, bivariate, multivariate), time series (ARIMA, ARCH), simulations (Monte Carlo method). 

Grasp the basics of probability theory and statistical methods. Being able to collect and interpret statistical data and to make a critical analysis of the results and measurements in technical engineering with appropriately chosen statistical methods. Use of some statistical data analysis software.

Lectures, laboratory work, homeworks, seminar assignment.