Course: Probability Models

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Course title Probability Models
Course code KMA/PMO
Organizational form of instruction Lecture
Level of course Master
Year of study not specified
Semester Winter and summer
Number of ECTS credits 5
Language of instruction Czech
Status of course Compulsory, Compulsory-optional
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Friesl Michal, Mgr. Ph.D.
  • Tomiczková Světlana, RNDr. Ph.D.
Course content
FOR WINTER TERM OF SCHOOL YEAR 2017/2018 1. From the theory of probability. 2. Stochastic process. 3. Poisson process. 4. Wiener process. 5. Markov chains with rewards. 6. Controlled chains. 7. Inventory and queuing theory I. 8. Inventory and queuing theory II. Additional information on the web page http://home.zcu.cz/~friesl/Vyuka/Pmo.html

Learning activities and teaching methods
Lecture supplemented with a discussion, Lecture with practical applications, Collaborative instruction, Group discussion, Task-based study method, Students' self-study, Self-study of literature, Lecture
  • Preparation for formative assessments (2-20) - 26 hours per semester
  • Contact hours - 52 hours per semester
  • Preparation for an examination (30-60) - 40 hours per semester
  • Presentation preparation (report) (1-10) - 20 hours per semester
prerequisite
professional knowledge
The course assumes knowledge of probability and statistics at least at the introductory course (KMA/PSA) level, more detailed knowledge of probability theory (KMA/TP) would be an advantage. The course also makes use of the apparatus of the other introductory mathematics courses (differential and integral calculus, matrices,...).
learning outcomes
To orientate oneself in treated properties of random processes, to be able to derive the results presented, to apply them in practical examples and draw practical conclusions.
teaching methods
Lecture
Lecture supplemented with a discussion
Task-based study method
Collaborative instruction
Group discussion
Students' self-study
Self-study of literature
Lecture with practical applications
assessment methods
Oral exam
Written exam
Report
Seminar work
Recommended literature
  • HUŠEK, R., LAUBER, J. Aplikace stochastických procesů I, učební text. Praha : VŠE, 1986.
  • HUŠEK, R., LAUBER, J. Simulační modely. 1. vyd. Praha : SNTL, 1987.
  • Mandl, Petr. Pravděpodobnostní dynamické modely : celost. vysokošk. učebnice pro stud. matematicko-fyz. fakult stud. oboru pravděpodobnost a matem. statistika. Praha : Academia, 1985.
  • Prášková, Zuzana; Lachout, Petr. Základy náhodných procesů. Praha : Karolinum, 1998. ISBN 80-7184-688-0.
  • Štěpán, Josef. Teorie pravděpodobnosti : Matematické základy : Vysokošk. učebnice pro stud. matematicko-fyz. fakult. Praha : Academia, 1987.


Study plans that include the course
Faculty Study plan (Version) Branch of study Category Recommended year of study Recommended semester
Faculty of Applied Sciences Financial Informatics and Statistics (2014) Economy 1 Summer
Faculty of Applied Sciences Financial Informatics and Statistics (2011) Economy 1 Summer
Faculty of Applied Sciences Information Systems (2016) Informatics courses 2 Summer
Faculty of Applied Sciences Information Systems (2013) Informatics courses 1 Summer
Faculty of Applied Sciences Financial Informatics and Statistics (2014) Economy 1 Summer
Faculty of Applied Sciences Information Systems (2015) Informatics courses 1 Summer
Faculty of Applied Sciences Training Teachers of Mathematics at Higher Secondary Scholls (2014) Pedagogy, teacher training and social care 1 Summer