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Course, academic year 2024/2025
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Mathematical Statistics - MS710P05
Title: Matematická statistika
Czech title: Matematická statistika
Guaranteed by: Institute of Applied Mathematics and Information Technologies (31-710)
Faculty: Faculty of Science
Actual: from 2024
Semester: summer
E-Credits: 2
Examination process: summer s.:
Hours per week, examination: summer s.:2/0, Ex [HT]
Capacity: 85
Min. number of students: unlimited
4EU+: no
Virtual mobility / capacity: no
State of the course: taught
Language: Czech
Note: enabled for web enrollment
priority enrollment if the course is part of the study plan
Guarantor: RNDr. Jitka Zichová, Dr.
Teacher(s): RNDr. Jitka Zichová, Dr.
Is co-requisite for: MS710C05
Annotation -
Basic concepts of probability theory and mathematical statistics: random event, probability, conditional probability, independence, correlation, random variable and its distribution, descriptive statistics, estimation of random variable characteristics, selected statistical tests. The lecture is oriented to understanding the subject with respect to applications in chemistry.
Last update: Zichová Jitka, RNDr., Dr. (27.01.2016)
Literature - Czech

Jiří Anděl: Statistické metody. Matfyzpress, Praha, 2007.

Jiří Anděl: Matematika náhody. Matfyzpress, Praha, 2000.

Karel Zvára, Josef Štěpán: Pravděpodobnost a matematická statistika. Matfyzpress, Praha, 2002.

Karel Zvára: Biostatistika. Karolinum, Praha, 2008.

Karel Zvára: Základy statistiky v prostředí R. Karolinum, Praha, 2013.

Last update: Zichová Jitka, RNDr., Dr. (27.01.2016)
Requirements to the exam - Czech

Zkouška je písemná v trvání 1 hodina. Studenti řeší sadu úloh s náplní danou sylabem předmětu. Požaduje se znalost definic základních pojmů, odvození jednoduchých vzorců, schopnost aplikovat teorii na řešení praktických příkladů, pochopení základních myšlenek pokročilejší statistiky (testování hypotéz, intervalové odhady, lineární regrese). Jedinou povolenou pomůckou je kalkulačka. Podrobné požadavky ke zkoušce lze nalézt na webové stránce vyučující.  

Last update: Zichová Jitka, RNDr., Dr. (05.05.2022)
Syllabus -

1) Introduction.

2) Descriptive statistics.

3) Basics of probability theory (random events, the definition of probability, conditional probability, independent events).

4) Random variable and its distribution. Characteristics of random variable. Examples of probability distributions.

5) Random vectors. Independent random variables, correlation. 

6) Random sample. The law of large numbers. The central limit theorem.

7) Probabilistic and statistical approach in exploring real world. Estimates of the random variable characteristics.

8) Estimation theory. Hypothesis testing. Mathematical statistics as a basic tool for drawing conclusions from a scientific experimental work.

9) Selected statistical tests (one sample test, two sample test, paired test, some nonparametric tests, independence testing in contingency table).

10) Linear regression model.

Last update: Zichová Jitka, RNDr., Dr. (07.04.2016)
 
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