13E082VS - Probability and Statistics
Course specification | ||||
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Course title | Probability and Statistics | |||
Acronym | 13E082VS | |||
Study programme | Electrical Engineering and Computing | |||
Module | ||||
Type of study | bachelor academic studies | |||
Lecturer (for classes) | ||||
Lecturer/Associate (for practice) | ||||
Lecturer/Associate (for OTC) | ||||
ESPB | 6.0 | Status | elective | |
Condition | Passed exams in Mathematics 1 and Mathematics 2 | |||
The goal | - Understanding applications of methods of Probability and Statistics in solving problems from real world, in particular in Automatic Control science. - Enabling students to solve various real world problems, applying the metods of Probability and Statistics, determining the correct mathematical model, and performing related parameter estimation and testing hypotheses | |||
The outcome | A student will be familiar with basic and moderately complex discrete and continuous stochastic models in the field of sygnals and systems. He/she will be able to apply correct models in real life problems, and to apply tools and methods of statistics and probability. | |||
Contents | ||||
URL to lectures | https://teams.microsoft.com/l/team/19%3aoLjCrp8E5UDQRTUEfCfFq2hIjwNWKFEdD2Q5Ew3uwoM1%40thread.tacv2/conversations?groupId=023dfa93-cc9f-4821-8b22-026a31abfaa2&tenantId=1774ef2e-9c62-478a-8d3a-fd2a495547ba | |||
Contents of lectures | Introduction and combinatorics. Conditional probability. Random variables. Numerical characteristics. Random vectors. Characteristic functions. Limit theorems. Parameter estimation. Hypotheses testing. Conditional distributions. Linear regression. Monte Carlo methods. | |||
Contents of exercises | Exercises with example and problem solving. | |||
Literature | ||||
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Number of hours per week during the semester/trimester/year | ||||
Lectures | Exercises | OTC | Study and Research | Other classes |
2 | 2 | 1 | ||
Methods of teaching | 30 hours of theoretical lecturing, 30 hours of exercises, 15 hours of discussion related to homework. | |||
Knowledge score (maximum points 100) | ||||
Pre obligations | Points | Final exam | Points | |
Activites during lectures | 0 | Test paper | 50 | |
Practical lessons | 0 | Oral examination | 0 | |
Projects | ||||
Colloquia | 30 | |||
Seminars | 20 |