# ESF:BPM_STA1 Statistics 1 - Course Information

## BPM_STA1 Statistics 1

**Faculty of Economics and Administration**

Autumn 2022

**Extent and Intensity**- 2/2/0. 5 credit(s). Type of Completion: zk (examination).

Taught in person. **Teacher(s)**- Mgr. Petra Ráboňová, Ph.D. (lecturer)

Ing. Matouš Cabalka (seminar tutor)

Mgr. Martin Dzúrik (seminar tutor)

Mgr. Lenka Franců (seminar tutor)

Mgr. Bc. Martin Chvátal, Ph.D. (seminar tutor)

Ing. Mgr. Markéta Matulová, Ph.D. (seminar tutor)

Mgr. Petra Ráboňová, Ph.D. (seminar tutor)

Ing. Mgr. Vlastimil Reichel, Ph.D. (seminar tutor)

Ing. Jana Vechetová (seminar tutor)

Mgr. Lenka Zavadilová, Ph.D. (seminar tutor)

Ing. Lukáš Kokrda (assistant) **Guaranteed by**- Mgr. Petra Ráboňová, Ph.D.

Department of Applied Mathematics and Computer Science - Faculty of Economics and Administration

Contact Person: Lenka Hráčková

Supplier department: Department of Applied Mathematics and Computer Science - Faculty of Economics and Administration **Timetable**- Tue 10:00–11:50 P101, except Tue 13. 9., except Tue 1. 11.
- Timetable of Seminar Groups:

*M. Chvátal*

BPM_STA1/04: Thu 16:00–17:50 VT202, except Thu 15. 9., except Thu 3. 11.,*M. Dzúrik*

BPM_STA1/06: Wed 14:00–15:50 S314, except Wed 14. 9., except Wed 2. 11.,*V. Reichel*

BPM_STA1/07: Wed 16:00–17:50 S314, except Wed 14. 9., except Wed 2. 11.,*V. Reichel*

BPM_STA1/09: Thu 12:00–13:50 S314, except Thu 15. 9., except Thu 3. 11.,*M. Chvátal*

BPM_STA1/11: Thu 14:00–15:50 VT202, except Thu 15. 9., except Thu 3. 11.,*M. Dzúrik*

BPM_STA1/13: Tue 12:00–13:50 VT206, except Tue 13. 9., except Tue 1. 11.,*M. Cabalka*

BPM_STA1/14: Tue 14:00–15:50 VT202, except Tue 13. 9., except Tue 1. 11.,*P. Ráboňová*

BPM_STA1/17: Wed 14:00–15:50 VT202, except Wed 14. 9., except Wed 2. 11.,*M. Cabalka*

BPM_STA1/19: Tue 16:00–17:50 VT202, except Tue 13. 9., except Tue 1. 11.,*M. Cabalka*

BPM_STA1/20: Wed 16:00–17:50 VT202, except Wed 14. 9., except Wed 2. 11.,*M. Cabalka*

BPM_STA1/23: Tue 12:00–13:50 VT202, except Tue 13. 9., except Tue 1. 11.,*P. Ráboňová*

BPM_STA1/24: Mon 18:00–19:50 VT202, except Mon 12. 9., except Mon 31. 10.,*M. Cabalka*

BPM_STA1/26: Fri 8:00–9:50 VT206, except Fri 16. 9., except Fri 4. 11.,*M. Dzúrik* **Prerequisites**(in Czech)- (
**BPM_MATE**Mathematics ) **Course Enrolment Limitations**- The course is also offered to the students of the fields other than those the course is directly associated with.
**fields of study / plans the course is directly associated with**- there are 13 fields of study the course is directly associated with, display
**Course objectives**- At the end of the course students should be able to:

- understand and explain the basic terms in calculus of probability and in descriptive statistics;

- apply the probability terms and the descriptive statistics terms to the description of economic events and data;

- use the terminology in the follow-up course of mathematical statistics. **Learning outcomes**- After graduation of the course student should be able to:

- use and interpret functional and numeric characteristics within a framework of descriptive statistics

- describe types of variables with respect to measurement scale

- quantify randomness in elementary setting by probability

- use and properly interpret distributional function, probability function and density function

- determine in mathematical statistics popular distributions with respect to the application context **Syllabus**- 1.Types of variables with respect to measurement scale. Data visualisation.
- 2. Sampling, random sample
- 3. Basic of descriptive statistics.
- 4. Frequency and probability, probability properties, examples.
- 5. Independent events, properties of independent events, sequence of independent events.
- 6. Conditional probability, total probability rule, Bayes' theorem, examples.
- 7. Random variable, a discrete and continuous variable, discrete probability distribution, probability function and its properties; continuous probability distribution, probability density function and its properties.
- 8. Distribution function, its properties and its application.
- 9. Numerical measures of probability distribution: expected value, variance, quantile, their properties and application in economics.
- 10. Numerical measures of simultaneous probability distribution: covariance, correlation coefficient, their properties and application in economics.
- 11. Examples of discrete and continuous probability distributions and their application in the field of economics.
- 12. Central limit theorem and its applications.
- 13. Review

**Literature**- BUDÍKOVÁ, Marie, Maria KRÁLOVÁ and Bohumil MAROŠ.
*Průvodce základními statistickými metodami (Guide to basic statistical methods)*. vydání první. Praha: Grada Publishing, a.s., 2010. 272 pp. edice Expert. ISBN 978-80-247-3243-5. URL info

*required literature*- WEISS, N. A.
*Introductory statistics*. Edited by Carol A. Weiss. 10th edition, global edition. Boston: Pearson, 2017. 763, 73. ISBN 9781292099729. info

*recommended literature*- BUDÍKOVÁ, Marie, Maria KRÁLOVÁ and Bohumil MAROŠ.
**Teaching methods**- Theoretical lectures; practical computer-aided seminar sessions;
**Assessment methods**- Lecture with a seminar

Test requirements:

1. Adequately active participation at seminars

2. Success at ROPOT tests

3. Success at final test

Any copying, recording or leaking tests, use of unauthorized tools, aids and communication devices, or other disruptions of objectivity of exams (credit tests) will be considered non-compliance with the conditions for course completion as well as a severe violation of the study rules. Consequently, the teacher will finish the exam (credit test) by awarding grade "F" in the Information System, and the Dean will initiate disciplinary proceedings that may result in study termination. **Language of instruction**- Czech
**Follow-Up Courses****Further comments (probably available only in Czech)**- The course is taught annually.

General note: Přednášky jsou dostupné online a ze záznamu. **Listed among pre-requisites of other courses****BKM_STA2**Statistics 2

(BKM_STA1) || (BPM_STA1) && forma(K)**BPM_STA2**Statistics 2

(BPM_STA1)**MPV_MZVS**Research Methods in the Public Sector

(( BPM_STA1 ) && (!MPV_KMZV))

- Enrolment Statistics (recent)

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