PřF:M7115 Mathematical modelling - semin - Course Information
M7115 Mathematical modelling - seminar
Faculty of ScienceAutumn 2016
- Extent and Intensity
- 0/2/0. 2 credit(s) (příf plus uk k 1 zk 2 plus 1 > 4). Type of Completion: z (credit).
- Teacher(s)
- doc. RNDr. Martin Kolář, Ph.D. (lecturer)
- Guaranteed by
- prof. RNDr. Zdeněk Pospíšil, Dr.
Department of Mathematics and Statistics – Departments – Faculty of Science
Supplier department: Department of Mathematics and Statistics – Departments – Faculty of Science - Timetable of Seminar Groups
- M7115/01: Mon 19. 9. to Sun 18. 12. Fri 8:00–9:50 M4,01024
- Prerequisites
- Calculus of one and several variables
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 22 student(s).
Current registration and enrolment status: enrolled: 0/22, only registered: 0/22, only registered with preference (fields directly associated with the programme): 0/22 - fields of study / plans the course is directly associated with
- Applied Mathematics for Multi-Branches Study (programme PřF, N-MA)
- Mathematical Analysis (programme PřF, N-MA)
- Mathematical Modelling and Numeric Methods (programme PřF, N-MA)
- Statistics and Data Analysis (programme PřF, N-MA)
- Course objectives
- The aim of the course is to teach students basics of bayesian analysis and its applications, mainly from the field of economics and finance. At the end of the course students should be able to: understand main ideas of bayesian probability and explain methods of their applications. They will be able to create a suitable model for a concrete problem and interpret predictions of such a model.
- Syllabus
- Basic notions of bayesian probability
- Applications in medical diagnostics
- Discrete parametric models
- Continuous parametric models
- Regression models
- Applications in neural networks
- Applications in game theory
- Applications in actuarial mathematics
- Literature
- OSBORNE, Martin J. An introduction to game theory. New York, N.Y.: Oxford University Press, 2004, xvii, 533. ISBN 9780195128956. info
- GELMAN, Andrew. Bayesian data analysis. 2nd ed. Boca Raton, Fla.: Chapman & Hall/CRC, 2004, xxv, 668. ISBN 158488388X. info
- OSBORNE, Martin J. and Ariel RUBINSTEIN. A course in game theory. Cambridge, Mass.: MIT Press, 1994, xv, 352. ISBN 0262150417. info
- MYERSON, Roger B. Game theory : analysis of conflict. Cambridge: Harvard University Press, 1991, xiii, 568. ISBN 0-674-34116-3. info
- Teaching methods
- Seminar lectures, class discussions
- Assessment methods
- Final test consisting of 10 questions. 50% of total points is needed to pass.
- Language of instruction
- Czech
- Further Comments
- Study Materials
The course is taught annually.
- Enrolment Statistics (Autumn 2016, recent)
- Permalink: https://is.muni.cz/course/sci/autumn2016/M7115