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Probability and Statistics II (CŽV) - NMUM813

Title:	Pravděpodobnost a statistika II (CŽV)
Guaranteed by:	Department of Mathematics Education (32-KDM)
Faculty:	Faculty of Mathematics and Physics
Actual:	from 2016 to 2017
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:	not taught
Language:	Czech
Teaching methods:	full-time
Teaching methods:	full-time
Is provided by:	NMUM404

Guarantor:	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
Incompatibility :	NUMP023
Interchangeability :	NUMP023
Is incompatible with:	NMUM404
Is interchangeable with:	NMUM404

Opinion survey results Examination dates Schedule Noticeboard

Annotation -

Last update: T_KPMS (14.05.2015)

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.

Aim of the course -

Last update: JUDr. Dana Macharová (10.10.2012)

To explain fundamentals of probability theory and mathematical statistics.

Literature - Czech

Last update: T_KPMS (14.05.2015)

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.

Teaching methods -

Last update: JUDr. Dana Macharová (10.10.2012)

Lecture+exercises.

Syllabus -

Last update: T_KPMS (14.05.2015)

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.