Basics of Stochastic

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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 time-table has been prepared for this course

The course is a part of the following study plans: