Czech

Not applicable.

Students will acquire basic knowledge of mathematical statistics, categorical and correlation analysis, analysis of variances, regression analysis and time series analysis.
At the end of the course students will be able to use these methods in master's courses and in the real managerial problems.

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):
- participation in seminars,
- elaboration of control tests and semestral assignments.

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:
- points achieved in control tests and semestral assignments,
- 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. Empirical characteristics
2. Empirical distribution function
3. Analysis of large data sets
4. Point and interval estimates
5. Testing statistical hypothesis
6. Correlation analysis
7. Categorical analysis
8. Analysis of variance
9. Linear regression models
10. Nonlinear regression models (linearizable functions)
11. Nonlinear regression models (non-linearizable functions)
12. Time series analysis
13. Time series decomposition and identify its trend

Not applicable.

Learning outcomes of the course unit is to acquaint students with the principal of mathematical statistics, categorical and correlation analysis, analysis of variances, regression analysis and time series analysis 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 B. 3. vyd. Brno: Akademické nakladatelství CERM, 2012. 152 s. ISBN 978-80-7204-822-9. (CS)
Studijní materiály vystavené na e-learningu.

BUDÍKOVÁ, M., T. LERCH a Š. MIKOLÁŠ. Základní statistické metody. 1. vyd. Brno: Masarykova univerzita v Brně, 2005. ISBN 80-210-3886-1.
FIELD, A., J. MILES and Z. FIELD. Discovering Statistics Using R. 1 edition. Los Angeles, Calif.: SAGE Publications Ltd., 2012. ISBN 978-1-4462-0046-9.
JAMES, G., D. WITTEN, T. HASTIE a R. TIBSHIRANI. An Introduction to Statistical Learning: with Applications in R. New York: Springer New York, 2014. 426 s. ISBN 978-1-4614-7137-0.