Course detail

Statistics

FP-STA1Acad. year: 2026/2027

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.

Language of instruction

Czech

Number of ECTS credits

6

Assignment to study programme types

Bachelor's

Mode of study

Not applicable.

Guarantor

Ing. Karel Doubravský, Ph.D.

Department

Department of Quantitative Engineering (ÚKI)

Entry knowledge

Combinatorics and calculus.

Rules for evaluation and completion of the course

Course Assessment

During the semester, students sit two assessment tests, for which they can earn a maximum of 30 points in total.

To pass the course, students must:

  • achieve a total of at least 15 marks from both assessment tests,
  • achieve a minimum of 80% active attendance in seminars.

Exam

The exam is written and carries a maximum of 70 marks. It consists of two parts:

  • practical part: 4 exercises, time limit 80 minutes, maximum 60 marks,
  • theoretical part: 2 theoretical questions, time limit 10 minutes, maximum 10 marks.

Overall assessment

The final mark is determined by the total number of marks obtained:

  • from the two assessment tests, a maximum of 30 marks,
  • from the examination paper, a maximum of 70 marks.

A maximum of 100 points can be obtained in total.

Grading
A ⟨90, 100⟩ points,
B ⟨80, 90) points,
C ⟨70, 80) points,
D ⟨60, 70) points,
E ⟨50, 60⟩ marks,
F ⟨0, 50⟩ marks.

Attendance at lectures is not mandatory, but is recommended. Attendance at seminars is monitored.
A student’s excused absence from a seminar may be made up by completing alternative assignments.

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.
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.

Study aids

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

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.

Recommended reading

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

Classification of course in study plans

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

Type of course unit

 

Lecture

26 hours, optionally

Teacher / Lecturer

doc. Mgr. Maria Králová, Ph.D.

Syllabus

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

Exercise

26 hours, compulsory

Teacher / Lecturer

doc. Mgr. Maria Králová, Ph.D.
Natálie Rontóová, Ph.D.

Syllabus

The topics of exercises correspond to the topics of lectures.

Self-study

60 hours, optionally

Teacher / Lecturer

Ing. Karel Doubravský, Ph.D.

Individual preparation for an ending of the course

44 hours, optionally

Teacher / Lecturer

Ing. Karel Doubravský, Ph.D.