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Course, academic year 2022/2023
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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 2022
Semester: winter
E-Credits: 8
Hours per week, examination: winter s.:4/2, 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
Additional information:
Guarantor: doc. RNDr. Michal Pešta, Ph.D.
Class: M Bc. FM
M Bc. FM > Povinné
Classification: Mathematics > Probability and Statistics
Pre-requisite : NMFM202
Is co-requisite for: NMFM310, NMFM308
Is pre-requisite for: NMFM332, NMFM334, NMFM336, NMFM338
Is interchangeable with: NSTP097
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.

Course completion requirements -
Last update: doc. RNDr. Michal Pešta, Ph.D. (28.10.2019)

Obtaining 'zápočet' (i.e. passing the tutorial) is a necessary condition for taking the examination.

It is granted by the teacher for (i) presence during the exercises (maximum of 2 unattended exercises allowed) and (ii) passing 2 written exams during the semester (at least 60% of points in each written pass exam).

There are no additional terms or possibilities for obtaining 'zápočet'.

The exam has a written and an oral part covering everything that is presented during the lectures. For more information see 'Requirements to the exam'.

Literature -
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

Casella G, Berger R.L.: Statistical Inference, 2nd Edition. Duxbury Thomson Learning, Pacific Grove, CA, 2002

Teaching methods -
Last update: G_M (24.04.2012)


Requirements to the exam -
Last update: doc. RNDr. Michal Pešta, Ph.D. (28.10.2019)

Obtaining "zápočet" (i.e. passing the tutorial) is a necessary condition for taking the examination.

We require knowledge of the concepts introduced in all the discussed fields, of their relations, and of all the performed proofs.

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.

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