PMSTAI Statistics I

Faculty of Economics and Administration
Autumn 2008
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)
Guaranteed by
RNDr. Marie Budíková, Dr.
Department of Applied Mathematics and Computer Science – Faculty of Economics and Administration
Contact Person: Lenka Hráčková
Timetable
Wed 12:50–14:30 P101, Wed 12:50–14:30 P102
  • Timetable of Seminar Groups:
PMSTAI/1: Wed 16:20–17:55 P312, M. Králová
PMSTAI/10: Thu 18:00–19:30 P103, T. Lerch
PMSTAI/11: Thu 7:40–9:15 P102, M. Králová
PMSTAI/12: Wed 16:20–17:55 S305, D. Hampel
PMSTAI/13: Wed 18:00–19:35 P303, D. Hampel
PMSTAI/14: Fri 7:40–9:15 P312, P. Krajíčková
PMSTAI/2: Wed 14:35–16:15 P304, M. Králová
PMSTAI/3: Thu 14:35–16:15 P106, P. Krajíčková
PMSTAI/4: Fri 9:20–11:00 S401
PMSTAI/5: Thu 11:05–12:45 P106, M. Králová
PMSTAI/6: Wed 18:00–19:35 P312, M. Králová
PMSTAI/7: Thu 7:40–9:15 P103, D. Hampel
PMSTAI/8: Fri 7:40–9:15 P303, D. Hampel
PMSTAI/9: Thu 16:20–17:55 P103, T. Lerch
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.
The capacity limit for the course is 404 student(s).
Current registration and enrolment status: enrolled: 0/404, only registered: 0/404, only registered with preference (fields directly associated with the programme): 0/404
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
Main objectives can be summarized as follows:
- to understand the basic terms in calculus of probability and the basic terms in descriptive statistics;
- to apply the probability terms and the terms in descriptive statistics in economics;
- to build the terminology for the course of mathematical statistics that follows;
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
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
Language of instruction
Czech
Follow-Up Courses
Further comments (probably available only in Czech)
The course is taught annually.
Information on course enrolment limitations: 10 pouze přednáška
The course is also listed under the following terms Spring 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007.
  • Enrolment Statistics (recent)
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