Lecturer(s)


Slavíček Ondřej, Mgr. Ph.D.

Brebera David, Mgr.

Čenčík Petr, Mgr.

Seinerová Kateřina, Ing.

Zapletal David, Mgr. Ph.D.

Heckenbergerová Jana, Mgr. Ph.D.

Course content

Introduction to statistics basic terms (frequency tables, pivot tables, graphs). Characteristics of quantitative variables (mean, variance, skewness, kurtosis). Statistics comparisons (Index analysis  simple and composite individual indices, the aggregate price and volume indices). Introduction to dependence investigation (coefficient of association, pivot coefficient and correlation coefficient). Introduction to regression analysis (linear regression model, index of determination, the regression line, parabolic regression etc.). Introduction to time series analysis (lemental characteristics of time series, classical decomposition of time series, modeling of trend and seasonal component). Probability theory (classical and statistical probabilty, conditional probability, independent events, probability theorem, Bayes' theorem, discrete and continuous random variables, characteristics of random variables, discrete distributions, continuous distributions). Central limit theorem, law of large numbers.

Learning activities and teaching methods

Monologic (reading, lecture, briefing), Dialogic (discussion, interview, brainstorming), Work with text (with textbook, with book)

Learning outcomes

The aim of the course is to teach students the principles of statistics and the basics of probability, so that they can be used both in most economic and administrative subjects, and practice in the evaluation of real situations. At the same time, students learn to work with statistical software Statictica.
Students will be able to apply statistical methods to solve practical problems in real situations.

Prerequisites

Successful completion of the course are in the range of knowledge of mathematics taught at universities.

Assessment methods and criteria

Home assignment evaluation, Student performance assessment, Systematic monitoring
Credit: successful passing of the tests (at least 60 %). Examination: written, consists of practical and theoretical tasks. Successful completion  at least 60 %.

Recommended literature


Arltová, Markéta . Základy statistiky v příkladech. Brno: Tribun EU, 2014. ISBN 9788026307563.

Brebera, David a kol. Sbírka příkladů ze statistiky. Pardubice, 2014.

Douglas C. Montgomery, George C. Runger. Applied statistics and probability for engineers, 4.vydání. John Wiley & Sons, Hoboken, 2007. ISBN ISBN 978047174.

Gibilisco, Stan. Statistics demystified : [a selfteaching guide]. New York: McGrawHill, 2004. ISBN 0071431187.

Hindls, R.,Hronová, S.,Seger, J. Statistika pro ekonomy. Praha, 2002.

Kubanová, Jana. Sbírka příkladů z pravděpodobnosti. Bratislava: Statis, 2004. ISBN 8085659360.

Linda, Bohdan. Pravděpodobnost. Pardubice: Univerzita Pardubice, 2010. ISBN 9788073953034.

Linda,B.Kubanová,J. Kritické hodnoty a kvantily vybraných rozdělení pravděpodobnosti. Univerzita Pardubice, 2006. ISBN 8071948527.

Mendehall, W.  Sincich, T. Statistics for Engineering and Sciences. New York, Macmillan Publishing Company 1992, 1992. ISBN 002946563X.

Milton, J. S., Arnold, J. Introduction to probability and statistics. New York, McGrawHill 2002, 2002.

PACÁKOVÁ, V. A KOL. Štatistické metódy pre ekonómov.. Bratislava: IURA Edition, 2009.

Selvin,S. Biostatistics: How it works. Pearson Education, PrenticeHall 2004, 2004. ISBN 0138046616.

Spiegel, M. R. Theory and Problems of Probability and Statistics. Singapore, McGrawsHill Book 1985, 1985. ISBN 007990301.
