SubjectsSubjects(version: 837)
Course, academic year 2018/2019
   Login via CAS
Practical Course in Probability Methods - NMAI165
Title in English: Praktikum z pravděpodobnostních metod
Guaranteed by: Department of Software Engineering (32-KSI)
Faculty: Faculty of Mathematics and Physics
Actual: from 2018
Semester: winter
E-Credits: 3
Hours per week, examination: winter s.:0/2 C [hours/week]
Capacity: unlimited
Min. number of students: unlimited
State of the course: taught
Language: Czech, English
Teaching methods: full-time
Guarantor: prof. RNDr. Jaromír Antoch, CSc.
Class: Informatika Mgr. - volitelný
Classification: Mathematics > Probability and Statistics
Annotation -
Last update: RNDr. Michal Kopecký, Ph.D. (12.05.2018)
The knowledge of ideas presented in the lecture NMAI060 Probability models will be deepened through solving more or less complicated problems with the eventual applications in the field of informatics. Basics of probability and knowledge obtained from the lecture is expected.
Aim of the course -
Last update: RNDr. Jitka Zichová, Dr. (14.05.2018)

The knowledge of ideas presented in the lecture NMAI060 Probability models will be deepened through solving more or less complicated problems with the eventual applications in the field of informatics.

Course completion requirements -
Last update: prof. RNDr. Jaromír Antoch, CSc. (05.10.2018)

Credits are granted for"

1. Active work during the classes.

2. Attendance in the classes: at most 30% absence.

Literature -
Last update: RNDr. Michal Kopecký, Ph.D. (12.05.2018)
  • Feller W., An Introduction to Probability Theory and its Applications, 3rd ed. J. Wiley, New York, 2008.
  • Prášková Z. a Lachout P. Základy náhodných procesů, Karolinum, Praha 1998.
  • Ross S.M. Introduction to Probability Models, 9th ed. Academic Press, Elsevier, London.

Teaching methods -
Last update: RNDr. Jitka Zichová, Dr. (14.05.2018)

Exercises.

Syllabus -
Last update: RNDr. Michal Kopecký, Ph.D. (12.05.2018)
  • Discrete and continuous random variables and their characteristics.
  • Recurrent events, their classification and applications.
  • Markov chains with discrete states and discrete time, classification of states, stationary distribution, etc.
  • Markov processes with discrete states and continuous time.
  • Models of birth and death.
  • Poisson process and its applications.
  • Basics of theory of queues, modeling of serving networks.
  • Exponential distribution and its use in the reliability theory.
  • Characteristics of reliability, survival times, intensity of failures and reliability of complex systems.

 
Charles University | Information system of Charles University | http://www.cuni.cz/UKEN-329.html