MU:MU03243 Probability and Statistics II - Course Information

MU03243 Probability and Statistics II

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., 2015, 689 pp. ISBN 978-1-118-79964-2. info
• 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

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.

• Enrolment Statistics (recent)
  
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