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Lecturer(s)
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Jindrová Pavla, Mgr. Ph.D.
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Čenčík Petr, Mgr.
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Linda Bohdan, doc. RNDr. CSc.
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Kubanová Jana, doc. PaedDr. CSc.
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Seinerová Kateřina, Ing.
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Brebera David, Mgr.
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Heckenbergerová Jana, Mgr. Ph.D.
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Course content
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Random sample and its classification, sample characteristics, quantiles. Empirical probability distribution Parameters estimation, point estimates, method of moments, method of maximal likelihood. Probability distribution of some sample characteristics. Confidence intervals for expected value and for variance. Hypothesis testing, significance testing for expected values and for variance. Good fitness test, Chi square test. Kolmogorov-Smirnov test, Lilliefors test. Nonparametric tests, sign test, Wilcoxon's test, outlier test, independence test and other. Regression analysis, linear regression, least squares method. Linear regression model for the function y = a+bf(x). Correlation analysis, Pearson´s and Spearman's correlation coefficient. Time series, its analysis - basic approaches, decomposition of time series. Time series smoothing, running averages, interlacing of functions. Economic statistics. Indices - basic and chained. Simple and compound individual indices, total indices.
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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)
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Learning outcomes
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The aim of the course is to acquaint the students with statistical principles in order to apply it in the majority of economic and administrative courses as well as in real situations.
Student will be able to apply statistical methods at solution of the practical problems and in real situations.
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Prerequisites
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Prerequisite for successful mastering of this subject is knowledge of mathematics and probability theory within the range taught at universities.
UMKM/PPAS1
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Assessment methods and criteria
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Oral examination, Written examination, Student performance assessment
Assignment-completion of all given tasks and passing all written tests with success minimum 50%. The exam consists of two parts - practical (counting of examples) and theoretical (demonstration of knowledge of the used terminology and understanding of used methods). Pass the exam involves acquiring at least 65% in each (practical and theoretical). If the student omits substantial part of the subject matter will be evaluated fail even if obtains more than 65% points in any part.
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Recommended literature
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Hill, T., Lewicki, P. Statistics: Methods and Applications. Tulsa, 2006. ISBN 80-86419-26-6.
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HINDLS R., HRONOVÁ S., SEGER J. Statistika pro ekonomy. 4.vydání, Professional Publishing, 2003..
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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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Kvanli,A.H., Pavur,R.J., Guynes,C.S. Introduction to Business Statistics - A Computer Integrated,Data Analysis Approach. New York, South-Western College Publishing, 2000, 2000. ISBN 0-324-01207-1.
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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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McClave,J., Benson, P., Sincich, T. Statistics for Bussiness and Economics. New York: Prentice Hall, 2001, 2001.
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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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Newbold, P. Statistics for Business and Economics. London, Prentice-Hall Int. Lim. 1991, 1991. ISBN 0138506450.
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Univerzita Pardubice. Ekonomickosprávní fakulta. Sbírka příkladů ze statistiky cvičebnice na CD. Pardubice: University of Pardubice Jan Perner Transport Faculty, 2014. ISBN 978-80-7395-854-1.
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Walpole, R.A. Introduction to Statistics. New York, Macmillan Publishers, 1989, 1989. ISBN 0-02-424150-4.
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