BPM_STA1 Statistics 1

Faculty of Economics and Administration
Autumn 2017
Extent and Intensity
2/2/0. 5 credit(s). Type of Completion: graded credit.
doc. Mgr. Maria Králová, Ph.D. (lecturer)
Mgr. Jan Böhm (seminar tutor)
Mgr. Terézia Černá (seminar tutor)
Mgr. Ondřej Černý (seminar tutor)
Mgr. Eva Janoušková, Ph.D. (seminar tutor)
Mgr. Štěpán Křehlík, Ph.D. (seminar tutor)
Ing. Mgr. Markéta Matulová, Ph.D. (seminar tutor)
Mgr. et Mgr. Alena Novotná (seminar tutor)
Mgr. Petra Ráboňová, Ph.D. (seminar tutor)
Ing. Mgr. Vlastimil Reichel, Ph.D. (seminar tutor)
Mgr. Tomáš Zdražil (seminar tutor)
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
Mon 16:20–17:55 P101
  • Timetable of Seminar Groups:
BPM_STA1/01: Wed 16:20–17:55 P103, O. Černý
BPM_STA1/02: Tue 11:05–12:45 S311, J. Böhm
BPM_STA1/03: Wed 18:00–19:35 P103, O. Černý
BPM_STA1/04: Thu 16:20–17:55 P201, Š. Křehlík
BPM_STA1/05: Tue 9:20–11:00 P106, J. Böhm
BPM_STA1/07: Wed 14:35–16:15 P304, J. Böhm
BPM_STA1/10: Thu 14:35–16:15 P201, T. Zdražil
BPM_STA1/11: Wed 18:00–19:35 P106, V. Reichel
BPM_STA1/13: Thu 12:50–14:30 P104, T. Zdražil
BPM_STA1/15: Wed 9:20–11:00 P201, J. Böhm
BPM_STA1/20: Thu 9:20–11:00 P103, Š. Křehlík
BPM_STA1/21: Mon 18:00–19:35 P201, M. Králová
BPM_STA1/23: Thu 11:05–12:45 P303, T. Zdražil
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 16 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.
  • 1.Frequency and probability, properties of probability, examples.
  • 2.Independent events, properties of independent events, sequence of independent events.
  • 3. Conditional probability, total probability rule, examples.
  • 4. Prior and posterior probabilities, Bayes' theorem, examples.
  • 5. Descriptive statistics, quantitative variables, qualitative variables; frequency distributions in tables and graphs, examples of data sets.
  • 6. Functional characteristics and numerical descriptive measures for univariate and multivariate quantitative variables, examples.
  • 7. Random variable, distribution function and its properties, discrete and continous variable, transformation of random variable.
  • 8. Discrete probability distribution, probability function and its properties; continuous probability distribution, probability density and its properties; random vector and its functional characteristics.
  • 9. Simultaneous and marginal random vectors, independent random variables, sequence of Bernoulli trials.
  • 10. Examples of discrete and continuous probability distributions and their application in the field of economics.
  • 11. Numerical measures of probability distribution: expected value, variance, quantile, their properties and application in economics.
  • 12. Numerical measures of simultaneous probability distribution: covariance, correlation coefficient, their properties and application in economics.
  • 13. Characteristics of random vectors, inequality theorems (Markov inequality theorem, Cebysev inequality theorem).
    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
  • BUDÍKOVÁ, Marie, Štěpán MIKOLÁŠ and Pavel OSECKÝ. Teorie pravděpodobnosti a matematická statistika.Sbírka příkladů. (Probability Theory and Mathematical Statistics.Collection of Tasks.). 2.dotisk 2.přeprac.vyd. Brno: Masarykova univerzita Brno, 2002. 127 pp. ISBN 80-210-1832-1. info
  • HANOUSEK, Jan and Pavel CHARAMZA. Moderní metody zpracování dat :matematická statistika pro každého. 1. vyd. Praha: Grada, 1992. 210 s. ISBN 80-85623-31-5. info
  • HINDLS, Richard, Stanislava HRONOVÁ and Jan SEGER. Statistika pro ekonomy. 4. vyd. Praha: Professional publishing, 2003. 415 s. ISBN 8086419525. info
Teaching methods
Theoretical lectures; practical seminar sessions;
Assessment methods
Lecture with a seminar
Graded credit requirements:
1. Adequately active participation at seminars
2. Success at progress test
3. Success at final test
A <90,100); B <80,90); C (<70,80); D <60,70); E <50,60); F <0,50) 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)
Study Materials
The course is taught annually.
General note: Přednášky jsou dostupné online a ze záznamu.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021.
  • Enrolment Statistics (Autumn 2017, recent)
  • Permalink: https://is.muni.cz/course/econ/autumn2017/BPM_STA1