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Course, academic year 2022/2023
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Methods of Mathematical Statistics - NMAI061
Title: Metody matematické statistiky
Guaranteed by: Department of Software Engineering (32-KSI)
Faculty: Faculty of Mathematics and Physics
Actual: from 2019
Semester: summer
E-Credits: 5
Hours per week, examination: summer s.:2/1, C+Ex [HT]
Capacity: unlimited
Min. number of students: unlimited
Virtual mobility / capacity: no
State of the course: taught
Language: Czech
Teaching methods: full-time
Guarantor: doc. RNDr. Zdeněk Hlávka, Ph.D.
Class: Informatika Mgr. - Teoretická informatika
Informatika Mgr. - Softwarové systémy
Informatika Mgr. - Matematická lingvistika
Classification: Mathematics > Probability and Statistics
Annotation -
Last update: T_KPMS (20.05.2009)
The main aim is to enhance the knowledge from the course Probability and statistics. Attention will be paid especially to the principles of estimation and hypothesis testing, to the theory and applications of the linear model, and to an overview of other useful statistical methods.
Aim of the course -
Last update: G_M (27.05.2008)

Basic statistical methods, estimation and testing and their use in practice will be presented.

Course completion requirements -
Last update: doc. RNDr. Zdeněk Hlávka, Ph.D. (06.10.2017)

Conditions for obtaining the credit (zápočet): active participation in the exercises and successful solving of a written assignment. The nature of the credit does not allow it to be repeated. Acquiring credit is a prerequisite for attending the exam.

Literature - Czech
Last update: doc. RNDr. Zdeněk Hlávka, Ph.D. (05.09.2012)

Anděl J., Statistické metody, MATFYZPRESS, Praha 1998.

Cipra T., Analýza časových řad s aplikacemi v ekonomii, SNTL/ALFA, Praha 1986.

Zvára K., Regrese, MATFZYPRESS, Praha 2008.

Teaching methods -
Last update: G_M (29.05.2008)


Requirements to the exam -
Last update: doc. RNDr. Zdeněk Hlávka, Ph.D. (06.10.2017)

The exam consists of a written and oral part. The written part is preceded by an oral part. Failing the written part means that the whole exam has been failed (and the oral part does not take place). Failing the oral part means that both the written and oral part of the exam must be repeated. The note is determined on the basis of both the written and the oral parts.

The written part consists of examples addressing topics corresponding both to what was presented during the lectures and exercises and to the syllabus of the subject.

Requirements for the oral part of the exam correspond to the syllabus of the subject in the scope that was presented at the lecture.

Syllabus -
Last update: doc. RNDr. Zdeněk Hlávka, Ph.D. (10.09.2013)

Random variable, normal distribution and some related distributions,

central limit theorem.

Random sample, estimator, maximum likelihood method, moment estimators,

confidence intervals, hypothesis testing, t-test, rank tests.

Random vectors, marginal and conditional distributions, graphical

display of multivariate data, multinormal distribution, principal


Linear model, polynomial regression, verification of assumptions,

residuals, leverage, time series analysis, contingency tables,

logistic regression, multivariate statistics.

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