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Statistics for Financial Mathematics - NMFM301

Title:	Statistika pro finanční matematiky
Guaranteed by:	Department of Probability and Mathematical Statistics (32-KPMS)
Faculty:	Faculty of Mathematics and Physics
Actual:	from 2015 to 2016
Semester:	winter
E-Credits:	8
Hours per week, examination:	winter s.:4/2, 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
Teaching methods:	full-time
Additional information:	http://www.karlin.mff.cuni.cz/~kulich/vyuka/statfpm/index.html

Guarantor:	doc. RNDr. Michal Pešta, Ph.D.
Class:	M Bc. FM M Bc. FM > Povinné
Classification:	Mathematics > Probability and Statistics
Incompatibility :	NSTP097
Pre-requisite :	NMFM202
Interchangeability :	NSTP097
Is co-requisite for:	NMFM310, NMFM308
Is interchangeable with:	NSTP097

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Annotation -

Last update: T_KPMS (13.05.2014)

Foundations of mathematical statistics for bachelor's students of Financial mathematics.

Aim of the course -

Last update: doc. Mgr. Michal Kulich, Ph.D. (05.09.2013)

Students will understand the foundations of mathematical statistics and important principles of parameter estimation and hypotheses testing. They will become familiar with most common statistical procedures and their application to real data.

Literature - Czech

Last update: doc. RNDr. Michal Pešta, Ph.D. (28.10.2019)

Anděl J.: Statistické metody. MATFYZPRES, Praha 1998

Anděl J.: Základy matematické statistiky. MATFYZPRES, Praha 2002

Teaching methods -

Last update: G_M (24.04.2012)

Lecture+exercises.

Syllabus -

Last update: doc. Mgr. Michal Kulich, Ph.D. (05.09.2013)

1. Random sample and its properties.

2. Point and interval estimators and their properties.

3. Parameter estimation methods. Empirical, moment estimators. Maximum likelihood.

4. Theory of hypotheses testing.

5. One-sample and paired methods for continuous data.

6. One-sample methods for discrete data.

7. Two-sample methods for continuous data.

8. Contingency tables.

9. Analysis of variance.

10. Linear regression.