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Lecturer(s)
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Course content
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1. Random event. 2. Random variable. 3. Random vector. 4. Function of random variables. 5. Number characteristics of random variables and random vectors. 6. Some distributions of discrete random variables. 7. Some distributions of continuous random variables I. 8. Some distributions of continuous random variables II. 9. Limit laws. 10. Introduction to mathematical statistics. 11. Elements of theory of estimation and elements of testing statistical hypotheses.
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Learning activities and teaching methods
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Lecture, Monologic Lecture(Interpretation, Training), Activating (Simulations, Games, Dramatization)
- Preparation for the Exam
- 600 hours per semester
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Learning outcomes
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This lecture provides the students with fundamental notions of the probability theory, especially with the concepts of a random variable and a multidimensional random variable. It presents some distributions of discrete random variables and continuous random variables. It completes this matter with the mathematical statistics based on the notion of a random sample, informs about elements of the estimation theory and the elements of the statistical hypothesis testing.
Knowledge. Define main notions, approaches, to be able to solve model problems.
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Prerequisites
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Basic knowledge of the undergraduate mathematics and physics.
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Assessment methods and criteria
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Mark, Oral exam, Systematic Observation of Student
Basic knowledge of mathematics.
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Recommended literature
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Anděl, J. (1986). Matematická statistika. SNTL, Praha.
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Hátle, L., Likeš, J. (1974). Základy počtu pravděpodobnosti a matematické statistiky. SNTL, Praha.
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Kunderová, P. (1997). Úvod do teorie pravděpodobnosti a matematické statistiky. UP Olomouc.
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