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Lecturer(s)
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Jindrová Pavla, Mgr. Ph.D.
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Zapletalová Lucie, Ing. Ph.D.
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Course content
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Exploratory data analysis. Moment statistical characteristics. Quantile statistical characteristics. Probabilistic models with application in the financial practice. Point estimates of selected probability models. Use of goodness-of-fit tests. Generalized Pareto distribution with applications in the financial practice. Probabilistic models of extreme values. Proportional numbers of development - absolute increments, growth coefficients, calculation of their averages. Chain and basic indices and their mutual relation. Indices are used in the financial sector.
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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), Skills training
- Home preparation for classes
- 75 hours per semester
- Preparation for an exam
- 23 hours per semester
- Participation in classes
- 52 hours per semester
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Learning outcomes
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The aim of the course is to expand students' knowledge of the course Probability and Statistics to selected statistical methods that have significant use in the financial sector, using software MS Excel and Statistics. Emphasis is placed on the ability of practical application of these methods and comprehensible and correct interpretation of the obtained results.
A student who has completed the course can: use exploratory data analysis tools; use probability models with applications in the financial field; use goodness-of-fit tests; characterize individual types of indices. A student who has completed the course will be able to: practically apply methods of exploratory data analysis and use selected probabilistic models for application tasks in the financial field using MS Excel or Statistica software; select, calculate and interpret appropriate indices used for statistical comparisons; interpret the obtained results. A student who has completed the course is able to: clearly and correctly communicate the content of the obtained results to the lay and professional public.
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Prerequisites
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The prerequisite for mastering the course is knowledge of high school mathematics.
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Assessment methods and criteria
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Home assignment evaluation, Student performance assessment, Systematic monitoring
Credit: Successfully completes the continuous written tests. Examination: oral and written. Detailed information can be found in the study resources.
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Recommended literature
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Bílková, Diana. Pravděpodobnost a statistika. Plzeň: Vydavatelství a nakladatelství Aleš Čeněk, 2009. ISBN 978-80-7380-224-0.
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BREBERA, D., JINDROVÁ, P., SEINEROVÁ, K., SLAVÍČEK, O., ZAPLETAL, D. Sbírka příkladů ze statistiky (cvičebnice na CD). 1. vydání. Pardubice: Univerzita Pardubice, 2014. ISBN 978-80-7395-854-1.
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Hendl, Jan. Přehled statistických metod zpracování dat : analýza a metaanalýza dat. Praha: Portál, 2004. ISBN 80-7178-820-1.
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Hendl, Jan. Základy matematiky, logiky a statistiky pro sociologii a ostatní společenské vědy v příkladech. Praha: Univerzita Karlova, nakladatelství Karolinum, 2022. ISBN 978-80-246-5400-3.
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Hindls, R. Hronová, S. Seger, J. Fischer,J. Statistika pro ekonomy. Praha: Professional Publishing, 2007. ISBN ISBN 978-80-86946.
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MELOUN M, MILITKÝ J. Kompendium statistického zpracování dat. 3. vyd. Praha: Karolinum, 2012.
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PACÁKOVÁ, V. a kol. Aplikovaná pojistná statistika. Pardubice: Univerzita Pardubice, 2019. ISBN 978-80-7560-259-6.
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Pacáková, Viera. Štatistické metódy pre ekonómov. Bratislava: Iura Edition, 2009. ISBN 978-80-8078-284-9.
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