Course detail

Statistics

FP-statPAcad. year: 2026/2027

CREDIT: Credit is awarded on the basis of:
- points for tests
- tests cannot be corrected!
EXAM: The exam is written, it consists of theory
The mark, corresponding to the sum (max. 100 points), consists of:
- from points for tests
- from points for the exam
- there is a requirement for a minimum score for the exam and credit
Marks and corresponding points:
A (100-90), B (89-80), C (79-70), D (69-60), E (59-50), F (49-0)


Attendance at lectures is not compulsory, 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.

Language of instruction

Czech

Number of ECTS credits

5

Assignment to study programme types

Bachelor's

Mode of study

Not applicable.

Guarantor

doc. Mgr. Veronika Novotná, Ph.D.

Department

Department of Quantitative Engineering (ÚKI)

Entry knowledge

Fundamentals of linear algebra and mathematical analysis.

Rules for evaluation and completion of the course

CREDIT: Credit is awarded on the basis of:
- points for tests
- tests cannot be corrected!
EXAM: The exam is written or oral, it consists of theory
The mark, corresponding to the sum (max. 100 points), consists of:
- from points for tests
- from points for the exam
- there is a requirement for a minimum score for the exam and credit
Marks and corresponding points:
A (100-90), B (89-80), C (79-70), D (69-60), E (59-50), F (49-0)

In the case of distance learning, when it will not be possible to write tests at the faculty during the semester:
- credit and exam will be solved on the basis of how long the full-time form of teaching will be maintained
- the effort will be that it is possible to implement credit tests in person at the faculty (even if the teaching takes place online), even within one day at the end of the semester


Attendance at lectures is not compulsory, 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.

Aims

The objective of the course is to make students familiar with the fundamentals of random variables, mathematical statistics, analysis of index numbers, regression analysis and time series. They will be able to study economic topics working with uncertainty, and to solve problems related to these topics applying the methods of this theory.
Students will be made familiar with the fundamentals of random variables, mathematical statistics, analysis of index numbers, regression analysis and time series and will learn how to use its methods to solve economic problemes. After completion of this course students will be prepared to study economic topics working with uncertainty.

Study aids

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

KROPÁČ, J. Statistika A. 5. vyd. CERM, Brno. 2013. ISBN 978-80-7204-835-9.
SEGER, J. aj. Statistické metody v tržním hospodářství. Praha : Victoria Publishing, 1995. ISBN 80-7187-058-7.

Recommended reading

HINDLS, R. aj. Analýza dat v manažerském rozhodování. Praha : Grada Publishing, 1999. ISBN 80-7169-255-7.
SWOBODA, H. Moderní statistika. Praha : Svoboda, 1977.

Classification of course in study plans

  • Programme BAK-EP Bachelor's 2 year of study, winter semester, compulsory, fundamental theoretical courses of the profile core
  • Programme BAK-PM Bachelor's 2 year of study, winter semester, compulsory
  • Programme BAK-UAD Bachelor's 2 year of study, winter semester, compulsory, profile core courses

Type of course unit

 

Lecture

13 hours, optionally

Teacher / Lecturer

Mgr. Eva Michalíková, Ph.D.

Syllabus

Topics of lectures are the following:
Classical definition of probability.
Conditioned probability.
Formula of total probability.
Random variables.
Random events.
Discrete random variables.
Continuous random variables.
Processing data samples.
Tests of statistical hypotheses.
Regression analysis.
Time series.

Exercise

26 hours, optionally

Teacher / Lecturer

Mgr. Eva Michalíková, Ph.D.
Ing. Matouš Cabalka
Natálie Rontóová, Ph.D.
Ing. Mgr. Anton Morozov

Syllabus

The topics of exercises correspond to the topics delt with the lectures.

Self-study

52 hours, optionally

Teacher / Lecturer

doc. Mgr. Veronika Novotná, Ph.D.

Individual preparation for an ending of the course

39 hours, optionally

Teacher / Lecturer

doc. Mgr. Veronika Novotná, Ph.D.