BPM_STA1 Statistics 1

Faculty of Economics and Administration
Autumn 2009
Extent and Intensity
2/2/0. 5 credit(s). Type of Completion: graded credit.
Teacher(s)
doc. Mgr. Maria Králová, Ph.D. (lecturer)
Mgr. David Hampel, Ph.D. (seminar tutor)
Mgr. Pavla Krajíčková, Ph.D. (seminar tutor)
doc. Mgr. Maria Králová, Ph.D. (seminar tutor)
Mgr. Tomáš Lerch (seminar tutor)
Ing. Mgr. Markéta Matulová, Ph.D. (seminar tutor)
RNDr. Václav Studený, Ph.D. (seminar tutor)
Guaranteed by
RNDr. Luboš Bauer, CSc.
Department of Applied Mathematics and Computer Science – Faculty of Economics and Administration
Contact Person: Lenka Hráčková
Timetable
Mon 9:20–11:00 P101
  • Timetable of Seminar Groups:
BPM_STA1/01: Wed 16:20–17:55 P312, T. Lerch
BPM_STA1/02: Tue 12:00–13:35 S311, M. Králová
BPM_STA1/03: Mon 12:50–14:30 VT314, M. Králová
BPM_STA1/04: Wed 16:20–17:55 S305
BPM_STA1/05: Mon 11:05–12:45 P103, M. Králová
BPM_STA1/06: Tue 13:45–15:20 S307, M. Králová
BPM_STA1/07: Wed 14:35–16:15 P304, V. Studený
BPM_STA1/08: Thu 14:35–16:15 P106, M. Matulová
BPM_STA1/09: Thu 11:05–12:45 P201, M. Králová
BPM_STA1/10: Thu 12:50–14:30 P106, M. Matulová
BPM_STA1/11: Wed 18:00–19:35 P312, T. Lerch
BPM_STA1/12: Thu 7:40–9:15 P103, D. Hampel
BPM_STA1/13: Thu 12:50–14:30 P104, M. Králová
BPM_STA1/14: No timetable has been entered into IS. P. Krajíčková
BPM_STA1/15: Wed 12:50–14:30 P102, V. Studený
BPM_STA1/16: No timetable has been entered into IS. P. Krajíčková
Prerequisites (in Czech)
PMMAT2 Mathematics II || PMZMII Introduction to Mathematics II
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 12 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.
Syllabus
  • 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).
Literature
  • OSECKÝ, Pavel. Statistické vzorce a věty (Statistical formulas). Druhé rozšířené. Brno (Czech Republic): Masarykova univerzita, Ekonomicko-správní fakulta, 1999, 53 pp. ISBN 80-210-2057-1. info
  • HINDLS, Richard, Stanislava HRONOVÁ and Jan SEGER. Statistika pro ekonomy. 4. vyd. Praha: Professional publishing, 2003, 415 s. ISBN 8086419525. 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
  • 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
  • BUDÍKOVÁ, Marie, Štěpán MIKOLÁŠ and Pavel OSECKÝ. Popisná statistika. 4th ed. Brno: Masarykova univerzita, 2007, 52 pp. ISBN 978-80-210-4246-9. 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 (80,89); C (70,79); D (60,69); E (50,59); F (0,49)
Language of instruction
Czech
Follow-Up Courses
Further comments (probably available only in Czech)
The course is taught annually.
General note: Nezapisují si studenti, kteří absolvovali předmět PMSTAI.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2010, Autumn 2011, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023.
  • Enrolment Statistics (Autumn 2009, recent)
  • Permalink: https://is.muni.cz/course/econ/autumn2009/BPM_STA1