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Lecturer(s)
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Pavlů Ivana, Mgr. Ph.D.
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Tomeček Jan, doc. RNDr. Ph.D.
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Fačevicová Kamila, Mgr. Ph.D.
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Fišerová Eva, doc. RNDr. Ph.D.
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Vencálek Ondřej, doc. Mgr. Ph.D.
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Andrášiková Aneta
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Course content
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1. History of probability. 2. Combinatorics. 3. Different models of a random experiment. 4. Definition of probability. Classical probability. 5. Geometric probability. 6. Axiomatic probability. 7. Independence. 8. Conditional probability. 9. Discrete and continuous random variable. 10. Probability distributions of a random variable. 11. Characteristics of location, scale and association. 12. Alternative, Binomial and Normal distributions.
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Learning activities and teaching methods
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Lecture, Monologic Lecture(Interpretation, Training), Dialogic Lecture (Discussion, Dialog, Brainstorming)
- Attendace
- 52 hours per semester
- Preparation for the Exam
- 70 hours per semester
- Homework for Teaching
- 30 hours per semester
- Preparation for the Course Credit
- 30 hours per semester
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Learning outcomes
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Mastering the principles of the probability theory.
Comprehension Mastering the principles of the probability theory.
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Prerequisites
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Knowledge of high school mathematics.
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Assessment methods and criteria
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Oral exam, Written exam
Credit: active participation in seminars, written test. Exam: the student has to present knowledge and understanding during the written and oral exam.
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Recommended literature
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J. L. Snell, C. M. Grinstead. (1997). Introduction to probability. Providence, RI: American Mathematical Society (AMS).
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K. Zvára, J. Štepán. (2006). Pravdepodobnost a matematická statistika. Matfyzpress, UK Praha.
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T. H. Wonnacot, R. J. Wonnacot. (1992). Statistika. Victoria Publishing, Praha.
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V. Dupač. (1984). Teorie pravděpodobnosti a matematická statistika. SPN, Praha.
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W. Chase, F. Bown. (1999). General statistics. John Wiley $ Sons.
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