Basics of Stochastic
Code  Completion  Credits  Range  Language 

E013066  Z  2  0P+2C 
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 Department of Technical Mathematics
 Synopsis:

Students will learn the basics of probability theory (random experiment, probability, random variable, probability distribution, characteristics of random variables, probability models, multivariate random variable and its characteristics, laws of large numbers and limit theorems) and the basic principles of statistical inference (frequency analysis, parameter estimation , hypothesis testing, regression analysis and more). The application of this knowledge we can found in all areas where it is necessary to evaluate the results of experiments, perform parameter estimation based on measurements, application of stochastic simulation methods, prediction of random processes and time series assessment. Also important is the use of these methods for the control of quality, reliability and risk assessment.
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 No timetable has been prepared for this course
 The course is a part of the following study plans: