KMSTAI Statistics I

Faculty of Economics and Administration
Autumn 2008
Extent and Intensity
0/0. 5 credit(s). Type of Completion: zk (examination).
Teacher(s)
Mgr. David Hampel, Ph.D. (lecturer)
RNDr. Marie Budíková, Dr. (alternate examiner)
Guaranteed by
doc. RNDr. Jaroslav Michálek, CSc.
Department of Applied Mathematics and Computer Science – Faculty of Economics and Administration
Contact Person: Lenka Hráčková
Timetable
Sat 4. 10. 8:30–11:50 P101, Sun 26. 10. 8:30–11:50 P101, Sat 22. 11. 8:30–11:50 P101
Prerequisites (in Czech)
KMMAT2 Mathematics 2 || KMMATB Mathematics B || C_KMMAT2 Mathematics
Course Enrolment Limitations
The course is only offered to the students of the study fields the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course consists of descriptive statistics (approximately 20 %), principles of probability theory (about 40 %) and statistical induction (about 40 %). The tutorials include motivation of the elementary concepts, key statements and calculation of typical examples. The topics follow a fixed procedure: descriptive statistical characteristics of nominal, ordinal, interval and proportional indicators; regression line; the basic properties of probability, stochastic independence of phenomena, conditional probability; random variables and vectors, their discrete and continuous type; joint distribution and stochastic independence of random variables; characteristics of random variables; asymptotic expressions; normal and other exact distributions; the basic concepts of statistical induction, double sample and paired comparison; confidence intervals; testing of hypotheses; regression analysis.

At the end of this course, students should be able to:
understand terms from probability and statistics; correctly present real data; apply basics of probability to simple real situations; use estimators and tests in the case when normally distributed data are anticipated; use system STATISTICA for solving real problems.
Syllabus
  • Basic, sample and data set
  • Point and interval frequency distribution
  • Numeral characteristic of marks
  • Regression line
  • Event and its probability
  • Stochastically independent events and conditional probability
  • Random variable and its distribution function
  • Selected distributions of discrete and continuous random variables
  • Numeral characteristics of random variables
  • Law of large numbers and Central limit theorem
  • Basic terms of mathematical statistics
  • Point and interval estimators of parameters and parametric functions
  • Introduction to hypothesis testing and tests about parameters of Normal distribution
Literature
  • BUDÍKOVÁ, Marie. Statistika. 1. vyd. Brno: Masarykova univerzita v Brně, 2004, 186 s. ISBN 8021034114. info
  • BUDÍKOVÁ, Marie, Štěpán MIKOLÁŠ and Pavel OSECKÝ. Popisná statistika (Descriptive Staistics). 2. dotisk 3. vydání. Brno: Masarykova univerzita v Brně, 2002, 52 pp. ISBN 80-210-1831-3. 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, Tomáš LERCH and Štěpán MIKOLÁŠ. Základní statistické metody. 1. vyd. Brno: Masarykova univerzita, 2005, 170 pp. ISBN 978-80-210-3886-8. info
  • Elementární statistická analýza. Edited by Lubomír Cyhelský - Jana Kahounová - Richard Hindls. 2. dopl. vyd. Praha: Management Press, 2001, 318 s. ISBN 80-7261-003-1. info
Assessment methods
Distance study. Lectures, self study. Written exam consisting of theoretical and practical parts, POT (final project corrected by tutor).
Language of instruction
Czech
Follow-Up Courses
Further comments (probably available only in Czech)
The course can also be completed outside the examination period.
The course is taught annually.
The course is also listed under the following terms Autumn 2006, Autumn 2007.
  • Enrolment Statistics (recent)
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