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Lecturer(s)
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Zapletal David, Mgr. Ph.D.
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Pacáková Viera, prof. RNDr. Ph.D.
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Slavíček Ondřej, Mgr. Ph.D.
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Jindrová Pavla, Mgr. Ph.D.
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Course content
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Basic statistical terms Statistical surveys, a specific examples of statistical survey (population census, Mikrocensus, public opinion research) Presentation of statistical data (presentation the values of qualitative and quantitative variables) Graphical analysis - bar chart, scatter chart, line chart, pie, polar, stock exchange-box plot) Data preparation for statistical processing Methods of analysis of qualitative data (single-stage and two-stage sorting, measurement of association of qualitative variables) Descriptive statistics-frequency distribution, frequency table, histogram The calculation of quantiles (quartiles, deciles, percentiles) Statistical characteristics of the level (position), variability, skewness and kurtosis of distribution Moments in the empirical dataset Regression analysis, linear model, transformable to linear models Multiple linear regressions Correlation analysis (coefficient of determination, correlation coefficient, the correlation ratio) Descriptive analysis of the time series, basic characteristics Regression models of the development trend The method of moving averages Seasonal indexes, seasonally adjusted time series. The relative number of development - individual indexes simple chain, basic 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
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Learning outcomes
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The course provides an introduction to statistical methods, deals with methodology for describing or summarizing a set of data using a table of frequency distribution, diagrams, and numerical measures. Subject describes the level/location, the variability, skewness and kurtosis of a set of data and investigates also linear relationships between variables using correlation analysis and regression analysis.
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
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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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Hendl, Jan. Přehled statistických metod zpracování dat : analýza a metaanalýza dat. Praha: Portál, 2004. ISBN 80-7178-820-1.
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HINDLS, R.,HRONOVÁ, S.,SEGER, J.:. Statistika pro ekonomy. Praha Professional Publishing, 2002. ISBN 80-86946-16-9.
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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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Pacáková, Viera. Štatistické metódy pre ekonómov. Bratislava: Iura Edition, 2009. ISBN 978-80-8078-284-9.
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WONNACOTT, T. H., WONNACOTT, R. J.:. Statistika pro obchod a hospodářství. Praha: Victoria Publishing, 1993.
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WONNACOTT,T.H., WONNACOTT,R.J.:. Introductory Statistics for Business and Economics. John Wiley, New York, 1984.
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