ESF:BPM_STA1 Statistics 1 - Course Information
BPM_STA1 Statistics 1Faculty of Economics and Administration
- Extent and Intensity
- 2/2/0. 5 credit(s). Type of Completion: zk (examination).
- doc. Mgr. Maria Králová, Ph.D. (lecturer)
Mgr. Jan Böhm (seminar tutor)
Ing. Matouš Cabalka (seminar tutor)
Mgr. Terézia Černá (seminar tutor)
Mgr. Monika Filová (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)
Mgr. Lenka Zavadilová, Ph.D. (seminar tutor)
Ing. Lukáš Kokrda (assistant)
- Guaranteed by
- doc. Mgr. Maria Králová, 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
- Tue 10:00–11:50 P101
- Timetable of Seminar Groups:
BPM_STA1/02: Thu 8:00–9:50 VT204, T. Černá
BPM_STA1/03: Wed 8:00–9:50 VT105, T. Černá
BPM_STA1/04: Thu 16:00–17:50 VT202, M. Matulová
BPM_STA1/05: Wed 12:00–13:50 VT105, T. Černá
BPM_STA1/06: Wed 14:00–15:50 VT105, J. Böhm
BPM_STA1/07: Wed 16:00–17:50 VT105, M. Cabalka
BPM_STA1/08: Wed 18:00–19:50 VT105, M. Cabalka
BPM_STA1/09: Thu 12:00–13:50 VT105, T. Černá
BPM_STA1/10: Thu 18:00–19:50 VT105, M. Chvátal
BPM_STA1/11: Thu 14:00–15:50 VT202, M. Matulová
BPM_STA1/12: Thu 16:00–17:50 VT105, M. Chvátal
BPM_STA1/13: Tue 12:00–13:50 VT206, J. Böhm
BPM_STA1/14: Tue 14:00–15:50 VT202, J. Böhm
BPM_STA1/15: Thu 18:00–19:50 VT206
BPM_STA1/16: Wed 18:00–19:50 VT202, J. Böhm
BPM_STA1/17: Wed 14:00–15:50 VT202, M. Chvátal
BPM_STA1/18: Wed 16:00–17:50 P104, M. Chvátal
- 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 22 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
- 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
- required 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
- recommended literature
- WEISS, N. A. Introductory statistics. Edited by Carol A. Weiss. 10th edition, global edition. Boston: Pearson, 2017. 763, 73. ISBN 9781292099729. info
- Teaching methods
- Theoretical lectures; practical computer-aided seminar sessions;
- Assessment methods
- Lecture with a seminar
1. Adequately active participation at seminars
2. Success at ROPOT tests
3. Success at progress test
4. 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
- 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