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Course, academic year 2023/2024
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Probabilistic and statistical problems - NMSA170
Title: Pravděpodobnostní a statistické problémy
Guaranteed by: Department of Probability and Mathematical Statistics (32-KPMS)
Faculty: Faculty of Mathematics and Physics
Actual: from 2023
Semester: summer
E-Credits: 2
Hours per week, examination: summer s.:0/2, C [HT]
Capacity: unlimited
Min. number of students: unlimited
Virtual mobility / capacity: no
State of the course: taught
Language: Czech
Teaching methods: full-time
Teaching methods: full-time
Guarantor: RNDr. Jiří Dvořák, Ph.D.
doc. RNDr. Zbyněk Pawlas, Ph.D.
Class: M Bc. FM
M Bc. FM > Doporučené volitelné
M Bc. FM > 1. ročník
M Bc. MMIT > Doporučené volitelné
M Bc. MMIT > 1. ročník
M Bc. OM
M Bc. OM > Doporučené volitelné
M Bc. OM > 1. ročník
Classification: Mathematics > Probability and Statistics
Annotation -
Last update: RNDr. Jitka Zichová, Dr. (24.04.2019)
Introduction to discrete probability and solutions of interesting problems by simple probabilistic and statistical methods. An elective course for 1st year students of General and Financial Mathematics.
Aim of the course -
Last update: RNDr. Jitka Zichová, Dr. (24.04.2019)

To acquaint students with the basic methods that are used to describe and study processes influenced by chance.

Course completion requirements -
Last update: doc. RNDr. Zbyněk Pawlas, Ph.D. (14.02.2022)

The course is finalized by receiving a credit.

Requirements for receiving the credit: active participation, max. 3 absences.

Attempt to receive the credit cannot be repeated.

Literature -
Last update: doc. RNDr. Zbyněk Pawlas, Ph.D. (28.10.2019)

J. Anděl (2007): Matematika náhody (in Czech), 3rd edition, Matfyzpress, Praha.

J. Bewersdorff (2005): Luck, Logic, and White Lies: The Mathematics of Games, A K Peters, Wellesley.

H. Tijms (2004): Understanding Probability: Chance Rules in Everyday Life, Cambridge University Press, Cambridge.

K. Zvára, J. Štěpán (2006): Pravděpodobnost a matematická statistika (in Czech), 4th edition, Matfyzpress, Praha.

Teaching methods -
Last update: doc. RNDr. Zbyněk Pawlas, Ph.D. (14.02.2022)


Syllabus -
Last update: RNDr. Jitka Zichová, Dr. (24.04.2019)

1. Random event with finitely many outcomes, classical probability and axiomatic definition.

2. Geometric probability.

3. Independence of random events, conditional probability, Bayes' theorem.

4. Discrete random variable, its distribution, expectation, variance.

5. Correlation, causality.

6. Hypotheses testing.

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