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Lecturer(s)
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Koucký Miroslav, doc. RNDr. CSc.
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Jirsák Čeněk, Mgr.
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Matoušek Jan, Ing.
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Chudoba Josef, Ing. Ph.D.
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Course content
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Introduction to probability theory (axiomatic definition, conditional probability, Bayes theorem, independence, discrete and continuous random variables, distribution function, prob. density function, random vectors, central limit theorem, law of large numbers). Introduction to mathematical statistics (point and interval estimation, hypotheses testing, linear regression, contingency table).
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Learning activities and teaching methods
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Monological explanation (lecture, presentation,briefing)
- Class attendance
- 56 hours per semester
- Preparation for exam
- 95 hours per semester
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Learning outcomes
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Students will learn fundamentals of probability theory, descriptive statistics and selected parts of mathematical statistics.
Theoretical knowledge and ability to apply them.
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Prerequisites
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Knowledge of the secondary level mathematics
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Assessment methods and criteria
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Combined examination
Active participation in seminars, credit, knowledge accordant with syllabus.
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Recommended literature
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Hebák, P.-Kahounová, J.:. Počet pravděpodobnosti v příkladech, Praha 1994.
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Kadeřábek, J. - Picek, J. Sbírka příkladů z pravděpodobnosti a statistiky. Liberec : Technická univerzita v Liberci, 2001. ISBN 80-7083-454-4.
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Likeš J., Machek J. Matematická statistika. SNTL, Praha 1983.
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Likeš, J., Machek, J. Počet pravděpodobnosti. Praha, SNTL 1981.
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