Czech

6

Not applicable.

Students will acquire basic knowledge of probability theory, random variables, random vectors, system reliability, index analysis, decision making under risk and uncertainty, descriptive statistics.
At the end of the course students will be able to use these methods in related subjects.

Not applicable.

Not applicable.

Teaching consists of lectures that have an explanation of basic principles and methodology of the discipline, practical problems and their sample solutions.
Exercise promote the practical knowledge of the subject presented in the lectures.

The course-unit credit is awarded on the following conditions (max. 40 points):
- elaboration of control tests.
-active participation in seminars 80% (any higher absence will be replaced by solving and submitting the additional examples).


The exam (max. 60 points)
- has a written form.
In the first part of the exam student solves 4 examples within 80 minutes. In the second part of the exam student works out answers to 3 theoretical questions within 15 minutes.

The mark, which corresponds to the total sum of points achieved (max. 100 points), consists of:
- of points achieved in control tests,
- points achieved by solving examples,
- points achieved by answering theoretical questions.

The grades and corresponding points:
A (100-90), B (89-83), C (82-76), D (75-69), E (68-60), F (59-0).

1. Classical probability
2. Conditional probability
3. Random variables
4. Discrete random variables
5. Continuous random variables
6. Theorem of Moivre-Laplace
7. Reliability of systems
8. Random vectors
9. Individual indices
10. Compound indexes
11. Decision making under risk
12. Decision trees
13. One-dimensional data sets of quantitative characters

Not applicable.

Learning outcomes of the course unit is to acquaint students with the basics of probability theory, random variables, index analysis, decision-making under risk and uncertainty and descriptive statistics so that they are able to apply this knowledge appropriately in management, informatics and economic problems.

Attendance at lectures is not mandatory, but is recommended. Attendance at exercises is required and checked by the tutor. An excused absence of a student from seminars can be compensated for by submitting solution of alternate exercises.

Not applicable.

Not applicable.

KROPÁČ, J. STATISTIKA A. 5. vyd. Brno: Fakulta podnikatelská, VUT v Brně, 2013. 140 s. ISBN 978-80-7204-835-9.
KROPÁČ, J. Statistika. 2. vyd. Brno: Akademické nakladatelství CERM, 2012. ISBN 978-80-7204-788-8.

HINDLS, R. aj. Analýza dat v manažerském rozhodování. Praha : Grada Publishing, 1999. ISBN 80-7169-255-7.
SWOBODA, H. Moderní statistika. Praha : Svoboda, 1977.
BUDÍKOVÁ, M., T. LERCH a Š. MIKOLÁŠ. Základní statistické metody. 1. vyd. Brno: Masarykova univerzita v Brně, 2005. ISBN 80-210-3886-1.
KROPÁČ, J. Statistika B. 2. vyd. Brno: Fakulta podnikatelská, 2009. ISBN 978-80-214-3295-6.

eLearning: currently opened course

26 hours, compulsory

The topics of exercises correspond to the topics of lectures.

eLearning: currently opened course