MU03243 Probability and Statistics II

Mathematical Institute in Opava
Summer 2019
Extent and Intensity
2/2/0. 6 credit(s). Type of Completion: zk (examination).
Teacher(s)
doc. Ing. Petr Seďa, Ph.D. (lecturer)
doc. Ing. Petr Seďa, Ph.D. (seminar tutor)
Guaranteed by
doc. Ing. Petr Seďa, Ph.D.
Mathematical Institute in Opava
Prerequisites (in Czech)
MU20009 Probability and Statistics I || MU01133 Probability and Statistics || MU10133 Probability and Statistics
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
Course objectives
To provide further attainments of mathematical statistics and essentials of stochastic processes theory.
Syllabus
  • Measurement of dependency of statistical variables.
    Test of independence in contingency tables. Contingency coefficients.
    Regression and correlation analysis
    Linear and non-linear regression. Regression with multiple parameters.
    Analysis of variance (ANOVA)
    with a single or multiple factors.
    Factor analysis
    Explorative factor analysis, principal component analysis (PCA).
    Confirmative analysis. Principal factor analysis.
    Cluster analysis
    Non-hierarchical, hierarchical clustering
    Time series analysis
    Transformation of uneven time series. Moving averages.
    Time series decomposition.
    Linear prediction.
    AR(p), MA(q) a ARMA(p,q) models.
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
    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
  • J. Likeš, J. Machek. Počet pravděpodobnosti. Praha, 1982. 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)
The course can also be completed outside the examination period.
Teacher's information
Requierements for pre-exam credits are defined by lecturer. In principle, students should be able to solve simple practical problems. During the course of exam, essential theoretical attainments are required.
The course is also listed under the following terms Summer 2008, Summer 2009, Summer 2010, Summer 2011, Summer 2012, Summer 2013, Summer 2014, Summer 2015, Summer 2016, Summer 2017, Summer 2018, Summer 2020, Summer 2021, Summer 2022, Summer 2023, Summer 2024.
  • Enrolment Statistics (Summer 2019, recent)
  • Permalink: https://is.slu.cz/course/sumu/summer2019/MU03243