Course detail

Statistics

Students will acquire basic knowledge of probability theory, random variables, random vectors, system reliability, index analysis, decision making under risk and uncertainty and descriptive statistics.

Learning outcomes of the course unit

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.

Prerequisites

Not applicable.

Co-requisites

Not applicable.

Recommended optional programme components

Not applicable.

KROPÁČ, J. STATISTIKA A. 5. vyd. Brno: Fakulta podnikatelská, VUT v Brně, 2013. 140 s. ISBN 978-80-7204-835-9.
HINDLS, R. aj. Analýza dat v manažerském rozhodování. Praha : Grada Publishing, 1999. ISBN 80-7169-255-7.
SWOBODA, H. Moderní statistika. Praha : Svoboda, 1977.
KROPÁČ, J. Statistika. 2. vyd. Brno: Akademické nakladatelství CERM, 2012. ISBN 978-80-7204-788-8.
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.

Planned learning activities and teaching methods

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.

Assesment methods and criteria linked to learning outcomes

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.

A (100-90), B (89-83), C (82-76), D (75-69), E (68-60), F (59-0).

Language of instruction

Czech

Work placements

Not applicable.

Course curriculum

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

Aims

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.

Specification of controlled education, way of implementation and compensation for absences

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.

Classification of course in study plans

• Programme BAK-MIn Bachelor's, 2. year of study, winter semester, 6 credits, compulsory

Type of course unit

Lecture

26 hours, optionally

Teacher / Lecturer

Exercise

26 hours, compulsory

Teacher / Lecturer

eLearning