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Lecturer(s)
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Jindrová Pavla, Mgr. Ph.D.
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Course content
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Basic statistical concepts. Methods of qualitative data analysis (one-dimensional and two-dimensional frequency distributions, graphical outputs, measurement of association and contingency of qualitative variables). Methods of quantitative data analysis (one-dimensional and two-dimensional frequency distributions, graphical outputs; calculation and interpretation of the quantiles; statistical characteristics of position, variability, skewness and kurtoses of distribution). Regression and correlation analysis (trend models of pairwise dependence; measures of intensity of pairwise dependence). Time series analysis (basic characteristics; regression trend models; moving average method; seasonal indexes, seasonally adjusted time series). Statistical comparisons (individual simple indexes, chained indexes, basic indexes, individual composite indexes, aggregate indexes).
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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
- Participation in classes
- 14 hours per semester
- Writing a seminar paper
- 50 hours per semester
- Preparation for an exam
- 22 hours per semester
- Participation in classes
- 52 hours per semester
- Home preparation for classes
- 26 hours per semester
- Participation in classes
- 14 hours per semester
- Home preparation for classes
- 64 hours per semester
- Home preparation for classes
- 64 hours per semester
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Learning outcomes
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The aim of the course is to apprise students with methods of data processing, presentation and analysis using descriptive statistics, basics of time series and statistical comparison, using MS Excel software, with emphasis on the ability of practical application of these methods and understandable and correct interpretation of obtained results.
A student who has successfully completed the course can: be familiar with basic statistical concepts; distinguish between different types of variables; select appropriate methods to describe the characteristics of a given data set; realize one-dimensional and two-dimensional distribution of frequencies, graphical outputs, and can also measure the association and contingency of qualitative traits; to realize one-dimensional and two-dimensional frequency distributions for graphical variables, graphical outputs. Furthermore, he can calculate and interpret quantiles, statistical characteristics of distribution, variability, skewness, and pointedness for these variables; to implement models of paired dependence trends and intensity of paired dependence; to implement regression models of development trend; practically apply descriptive statistics methods, time series basics and statistical comparison using MS Excel software; select, calculate and interpret appropriate indexes used for statistical comparison.
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Prerequisites
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The prerequisite for mastering the subject is knowledge of the mathematics of high school .
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Assessment methods and criteria
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Home assignment evaluation, Student performance assessment, Systematic monitoring
Credit: elaboration and defense of seminar work, which represents processing of data file with the use of individual discussed methods on the subject, using MS Excel. Examination: oral and written.
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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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Budíková, Marie. Průvodce základními statistickými metodami. Praha: Grada, 2010. ISBN 978-80-247-3243-5.
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CYHELSKÝ, L., SOUČEK, E. Základy statistiky. Praha: EUPRESS, 2009.
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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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Pacáková, Viera. Štatistické metódy pre ekonómov. Bratislava: Iura Edition, 2009. ISBN 978-80-8078-284-9.
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