MU:MU03243 Probability and Statistics II - Course Information
MU03243 Probability and Statistics II
Mathematical Institute in OpavaSummer 2022
- Extent and Intensity
- 2/2/0. 6 credit(s). Type of Completion: zk (examination).
- Teacher(s)
- doc. Ing. Petr Seďa, Ph.D. (lecturer)
- Guaranteed by
- RNDr. Oldřich Stolín, Ph.D.
Mathematical Institute in Opava - Timetable
- Thu 13:55–15:30 LVT1
- Timetable of Seminar Groups:
- Prerequisites (in Czech)
- ( MU20009 Probability and Statistics I || MU01133 Probability and Statistics || MU10133 Probability and Statistics ) && ! MU03143 Probability and Statistics II && !NOW( MU03143 Probability and Statistics II ) && TYP_STUDIA(B)
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Applied Mathematics (programme MU, B1101)
- Applied Mathematics in Risk Management (programme MU, B1101)
- Mathematical Methods and Modelling (programme MU, Bc-M)
- Mathematical Methods in Economics (programme MU, B1101)
- Mathematical Methods in Economics (programme MU, Bc-M)
- Mathematical Methods in Risk Management (programme MU, Bc-M)
- General Mathematics (programme MU, Bc-M)
- Mathematics (programme MU, B1101)
- Course objectives
- The second part of the two-semestral course aims at fundamental methods and principles of mathematical statistics (descriptive and inferential).
- Syllabus
- 1. Exploratory data analysis: basic methods of analysis of data, numerical characteristics, contingency tables.
2. Point and interval estimates. Method of maximal likelihood.
3. Hypothesis testing: basic principles, parametric and nonparametric tests.
4. General linear model and its selected special cases: analysis of variance (ANOVA), factor analysis, linear regression.
5. Nonlinear regression, cluster analysis.
6. Analysis of time series.
- 1. Exploratory data analysis: basic methods of analysis of data, numerical characteristics, contingency tables.
- Literature
- required literature
- RUBLÍKOVÁ, Eva. Analýza časových radov. Bratislava: Ekonomická univerzita, 2007. Iura Edition. ISBN 978-80-8078-139-2. info
- Anděl J. Statistické metody. MatFyzPress, Praha, 2007. ISBN 80-7378-001-1. info
- Anděl J. Základy matematické statistiky. MatFyzPress, Praha, 2007. ISBN 80-7378-003-8. info
- HENDL, Jan. Přehled statistických metod zpracování dat. Praha: Portál., 2004. ISBN 80-7178-820-1. info
- C. R. Rao, H. Toutenburg. Linear Models. Springer New York, 1995. info
- recommended literature
- BROCKWELL. Peter J. a Richard A. DAVIS. Time Series: Theory and Methods. Springer, 2nd ed., 2009. ISBN 978-1441903198. info
- ŘEZANKOVÁ, H., HÚSEK, D. a SNÁŠEL, V. Shluková nalýza dat. Professional Publishing Praha., 2007. ISBN 978-80-86946-26-9. info
- MELOUN, Milan a Jiří MILITKÝ. Kompendium statistického zpracování dat: metody a řešené úlohy. Academia, Praha., 2006. ISBN 80-200-1396-2. info
- Riečanová a kol. Numerické metody a matematická štatistika. Alfa, Bratislava., 1987. ISBN 063-559-87. info
- J. Likeš, J. Machek. Matematická statistika. Praha, 1983. info
- not specified
- F. S. Hilier, G. J. Lieberman. Introduction to stochastic models in operations reseach. McGraw Hill, 1990. info
- Language of instruction
- Czech
- Further comments (probably available only in Czech)
- Study Materials
The course can also be completed outside the examination period. - Teacher's information
- The final exam consists of a written (at least 60%) and an oral part (2 theoretical questions). To obtain the pre-exam credits it is neccessary to actively participate in seminars on a regular basis and passing two written tests (60% at least).
- Enrolment Statistics (Summer 2022, recent)
- Permalink: https://is.slu.cz/course/sumu/summer2022/MU03243