MU03243 Probability and Statistics II

Mathematical Institute in Opava
Summer 2024
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
doc. Ing. Petr Seďa, Ph.D.
Mathematical Institute in Opava
Timetable
Thu 8:55–10:30 LVT1
  • Timetable of Seminar Groups:
MU03243/01: Thu 10:35–12:10 LVT1, P. Seďa
Prerequisites
( 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 )
This subject requires knowledge of probability theory.
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
there are 8 fields of study the course is directly associated with, display
Course objectives
The second part of the two-semestral course aims at fundamental methods and principles of mathematical statistics (descriptive and inferential). Attention will also be given to the multivariate statistical methods and the basics of time series analysis.
Learning outcomes
Students will learn to choose and use the selected statistical methods and interpret statistical results. In addition, they will learn how these methods can be used in practice and also in relation to the theses.
Syllabus
  • 1. Exploratory data analysis: basic data processing methods, and numerical characteristics.
    2. Verification of the probability distribution. The goodness of fit tests.
    3. One-sample and two-sample tests.
    4. Measurement of dependencies of qualitative data. Contingency and association tables.
    5. Correlation and simple regression.
    6. Multiple regression and logistic regression.
    7. Analysis of variance - ANOVA.
    8. Factor analysis.
    9. Cluster analysis.
    10. Introduction to time series analysis.
    11. Analytical and synthetic models of time series.
    12. Box-Jenkinson methodology.
Literature
    required literature
  • ROHATGI, V. K. and A. K. M. E. SALEH. An Introduction to Probability and Statistics. 3rd edition. Hoboken, New Jersey: John Wiley & Sons, Inc. 689 pp. ISBN 978-1-118-79964-2. 2015. info
  • RUBLÍKOVÁ, Eva. Analýza časových radov. Bratislava: Ekonomická univerzita. Iura Edition. ISBN 978-80-8078-139-2. 2007. info
  • Anděl J. Statistické metody. MatFyzPress, Praha. ISBN 80-7378-001-1. 2007. info
  • Anděl J. Základy matematické statistiky. MatFyzPress, Praha. ISBN 80-7378-003-8. 2007. info
  • HENDL, Jan. Přehled statistických metod zpracování dat. Praha: Portál. ISBN 80-7178-820-1. 2004. info
    recommended literature
  • BROCKWELL. Peter J. a Richard A. DAVIS. Time Series: Theory and Methods. Springer, 2nd ed. ISBN 978-1441903198. 2009. info
  • ŘEZANKOVÁ, H., HÚSEK, D. a SNÁŠEL, V. Shluková nalýza dat. Professional Publishing Praha. ISBN 978-80-86946-26-9. 2007. info
  • MELOUN, Milan a Jiří MILITKÝ. Kompendium statistického zpracování dat: metody a řešené úlohy. Academia, Praha. ISBN 80-200-1396-2. 2006. info
  • Riečanová a kol. Numerické metody a matematická štatistika. Alfa, Bratislava. ISBN 063-559-87. 1987. info
  • J. Likeš, J. Machek. Matematická statistika. Praha, 1983. info
Teaching methods
Lecture (2 hours) and seminars (2 hours) every week.
Assessment methods
The exam consists of an oral part. The oral part contains two theoretical questions that the applicant must answer. Regular active participation in the seminars and mastering the practical test (at least 67%) are required to obtain credit.
Language of instruction
Czech
Further Comments
Study Materials
The course can also be completed outside the examination period.
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 2019, Summer 2020, Summer 2021, Summer 2022, Summer 2023.
  • Enrolment Statistics (recent)
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