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Lecturer(s)
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Zapletalová Lucie, Ing. Ph.D.
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Zapletal David, doc. Mgr. Ph.D.
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Heckenbergerová Jana, Mgr. Ph.D.
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Course content
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Hyphotheses testing Analysis of variance. Nonparametric ANOVA. Analysis of dependence of random variables Classical linear regression model. Violation of the basic conditions of the linear model (heteroscedasticity, autocorrelation, multicolinearity). Selected non-linear models not transferable to linear form. Logictic regression and its aplications. Discriminate analysis. Cluster analysis. Principal component analysis and Factor analysis
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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)
- Preparation for an exam
- 35 hours per semester
- Contact teaching
- 65 hours per semester
- Preparation for a credit (assessment)
- 25 hours per semester
- Home preparation for classes
- 25 hours per semester
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Learning outcomes
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The aims of the subject is to acquaint student with other advanced methods of mathematical statistics, above all multidimensional statistics and with econometrics principles.
Student who has successfully completed the course can: describe real processes using random variables, explain the nature of advanced statistical methods. Student who has successfully completed the course is skilled: to decide correctly about the solution method, to evaluate correctly the conclusions of statistical analyzes, to apply statistical methods, to solve specific tasks, to evaluate data and to interpret conclusions to solve problems in economic and other sciences, including methodology of data processing and evaluation. The student who has successfully completed the course is able to: consider in intention of mathematical statistics, independent solution of data-based problems, using appropriate statistical software to model and evaluate processes related to economic and social phenomena communicate intelligently the results of statistical analysis.
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Prerequisites
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Prerequisite for successful mastering of this subject is knowledge of mathematics, probability theory and statistics within the range taught at universities fosud on economics.
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Assessment methods and criteria
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Oral examination, Written examination, Student performance assessment
Assignment-successful completion of a control test (solving problems with the help of computer) in the last week of the semester. It is necessary to obtain at least 60 points out of 100 possible. Exam - successful completion of a written control test, which verifies basic knowledge of the statistical methods discussed. It is necessary to obtain at least 60 points out of 100 possible.
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Recommended literature
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Anděl,J. Matematická statistika. Praha: SNTL, 1978.
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Cipra, Tomáš. Finanční ekonometrie. Praha: Ekopress, 2013. ISBN 978-80-86929-93-4.
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HATRÁK, M. Ekonometria.. Bratislava: Iura Edition, 2007.
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HEBÁK, P. a kol. Vícerozměrné statistické metody (1). Praha: Informatorium, (2004), ISBN 80-7333-025-3..
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HEBÁK, P. a kol. Vícerozměrné statistické metody (2). Praha: Informatorium, (2007), ISBN 978-80-73333-001-9..
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HEBÁK, P. a kol. Vícerozměrné statistické metody (3). Praha: Informatorium, (2007), ISBN 978-80-73333-001-9..
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McCLAVE, J., BENSON, P., SINCICH, T. Statistics for Business and Economics. New York Prentice Hall, 2001.
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Meloun, M. a kol. Statistická analýza vícerozměrných dat v příkladech. Praha, 2017. ISBN 978-80-246-3618-4.
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MENDEHALL, W., SINCICH, T. Statistics for Engineering and Sciences. New York: Maxmillan Publishing Company, 1992.
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Newbold, P. Statistics for Business and Economics. London: Prentice-Hall Int. Lim. 1991, 1991. ISBN 0138506450.
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Víšek,J.,A. Statistická analýza dat. ČVUT 1998, 1998.
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