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Probability and statistics II - NMUM404

Title:	Pravděpodobnost a matematická statistika II
Guaranteed by:	Department of Mathematics Education (32-KDM)
Faculty:	Faculty of Mathematics and Physics
Actual:	from 2015 to 2015
Semester:	summer
E-Credits:	3
Hours per week, examination:	summer s.:2/1, C+Ex [HT]
Capacity:	unlimited
Min. number of students:	unlimited
4EU+:	no
Virtual mobility / capacity:	no
State of the course:	taught
Language:	Czech
Teaching methods:	full-time

Guarantor:	RNDr. Jitka Zichová, Dr.
Teacher(s):	RNDr. Jakub Staněk, Ph.D. RNDr. Jitka Zichová, Dr.
Class:	Učitelství matematiky
Classification:	Mathematics > Mathematics, Algebra, Differential Equations, Potential Theory, Didactics of Mathematics, Discrete Mathematics, Math. Econ. and Econometrics, External Subjects, Financial and Insurance Math., Functional Analysis, Geometry, General Subjects, , Real and Complex Analysis, Mathematics General, Mathematical Modeling in Physics, Numerical Analysis, Optimization, Probability and Statistics, Topology and Category, Probability and Statistics Teaching > Mathematics
Co-requisite :	NMUM403
Incompatibility :	NUMP023
Interchangeability :	NUMP023
Is incompatible with:	NUMP023
Is interchangeable with:	NUMP023

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Annotation -

A course for future teachers of mathematics. Law of large numbers, central limit theorem. Random vectors. Descriptive statistics, correlation. Point and interval parameter estimates. Hypothesis testing in a random sample from normal distribution. Linear model. Contingecy tables.

Last update: Zichová Jitka, RNDr., Dr. (14.05.2020)

Aim of the course -

To explain basics of probability theory and mathematical statistics.

Last update: T_KPMS (12.05.2015)

Literature - Czech

Zvára, K., Štěpán, J: Pravděpodobnost a matematická statistika. Matfyzpress, Praha, 2002.

Anděl, J.: Základy matematické statistiky. Matfyzpress, Praha, 2005.

Anděl, J.: Statistické metody. Matfyzpress, Praha, 1993 a další vydání.

Last update: Zichová Jitka, RNDr., Dr. (16.04.2018)

Teaching methods -

Lecture+exercises.

Last update: T_KPMS (12.05.2015)

Syllabus -

Law of large numbers, central limit theorem.

Random vectors.

Descriptive statistics, correlation.

Point and interval parameter estimates.

Hypothesis testing in a random sample from a normal distribution.

Linear model.

Contingency tables.

Last update: T_KPMS (12.05.2015)