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Lecturer(s)
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Brebera David, Mgr.
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Kubanová Jana, doc. PaedDr. CSc.
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Zapletal David, Mgr. Ph.D.
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Slavíček Ondřej, Mgr. Ph.D.
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Čenčík Petr, Mgr.
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Course content
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Basis of descriptive statistics, statistical characteristics. Sample and its classification, sample characteristics, quantiles. Random events (definitions of basic terms).Term probability and its interpretation. Conditional probability, independence of events, conditional probability probability theorem, Bayes' theorem. Bernoulli independent repeated experiments. One-dimensional random variable, probability distribution, distribution function, discrete and continuous random variable, probability density. Common probability distributions, important for economical applications. Multidimensional random variable, marginal distribution function, independent random variables. Characteristics of one-dimensional and multidimensional random variables, measure of interdependence(expected value, variance, covariance) Probability distribution of some sample characteristics. Stochastic dependence, regression and correlation. Limit theorems - laws of large numbers, central limit theorem.
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), Dialogic (discussion, interview, brainstorming), Work with text (with textbook, with book)
- unspecified
- 52 hours per semester
- unspecified
- 10 hours per semester
- unspecified
- 10 hours per semester
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Learning outcomes
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The aim of the course is to acquaint the students with theoretical essentials for the follow-up mathematical and first of all for the specialized courses of the economic character.
Students will be able to apply methods of the probability theory in encountering practical tasks as well as in real situations.
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Prerequisites
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Prerequisite for mastering of the subject PPAS1 is knowledge of the subjects mathematics 1 and mathematics 2.
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Assessment methods and criteria
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Home assignment evaluation, Student performance assessment, Systematic monitoring
Assignment-completion of all given tasks and passing of two written tests.
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Recommended literature
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Gibilisco, Stan. Statistics demystified : [a self-teaching guide]. New York: McGraw-Hill, 2004. ISBN 0-07-143118-7.
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Kubanová, Jana. Probability. Pardubice: Univerzita Pardubice, 2007. ISBN 978-80-7194-934-3.
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Kubanová, Jana. Sbírka příkladů z pravděpodobnosti. Bratislava: Statis, 2004. ISBN 80-85659-36-0.
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Kubanová, Jana. Statistické metody pro ekonomickou a technickou praxi. Bratislava: Statis, 2008. ISBN 978-80-85659-47-4.
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Kubanová, Jana. Teorie pravděpodobnosti. Pardubice: Univerzita Pardubice, 1999. ISBN 80-7194-193-X.
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Linda, Bohdan. Pravděpodobnost. Pardubice: Univerzita Pardubice, 2010. ISBN 978-80-7395-303-4.
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Linda,B.-Kubanová,J. Kritické hodnoty a kvantily vybraných rozdělení pravděpodobnosti. Univerzita Pardubice, 2006. ISBN 80-7194-852-7.
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Mendehall, W. - Sincich, T. Statistics for Engineering and Sciences. New York, Macmillan Publishing Company 1992, 1992. ISBN 002946563X.
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Milton, J. S., Arnold, J. Introduction to probability and statistics. New York, McGraw-Hill 2002, 2002.
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Pacáková, Viera. Štatistické metódy pre ekonómov. Bratislava: Iura Edition, 2009. ISBN 978-80-8078-284-9.
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Selvin,S. Biostatistics: How it works. Pearson Education, Prentice-Hall 2004, 2004. ISBN 0-138-046616-.
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Spiegel, M. R. Theory and Problems of Probability and Statistics. Singapore, McGraws-Hill Book 1985, 1985. ISBN 007990301.
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