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Lecturer(s)
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Mrkvička Tomáš, prof. RNDr. Ph.D.
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Klicnarová Jana, doc. RNDr. Ph.D.
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Course content
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Content of the subject: 1. Classification of models from different perspectives. Linear programming, sensitivity analysis, parametric linear programming, multicriteria optimization. Transport tasks, including special types. 2. Structural analysis. Analysis of data packaging and its application. Stochastic and deterministic network models. Models of Conflict Situations and Theory. 3. Stochastic models and a simulation approach to their solution. Multi-criteria evaluation of variants, selection issues. Software support for basic types of mathematical models used in management and decision making (EXCEL and its modules, LINGO, @RISK, MS Project). 4. Modern methods of time series analysis. 5. Analysis of major components. 6. Methods of cluster analysis, discriminatory analysis and multidimensional analysis of variance. 7. Econometric models. Classical model of linear regression and its generalization, violation of assumptions, heteroskedasticity, autocorrelation. 8. Special Models of Linear Regression - Discrete Models, Logistic and Poisson Regression. 9. Multiline models of linear regression, structural and reduced shape, model identification. 10. Application of econometric models in practice.
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Learning activities and teaching methods
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unspecified
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Learning outcomes
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The aim of the course is to extend the knowledge of the students in the area of using mathematical-statistical methods in economy and control methods. The students will learn how to apply these methods on the theme of their scientific project. The importance is taken especially on good interpretation of the results. The course has two semesters.
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Prerequisites
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The students have to understand to the chosen methods and they have to apply the methods for solving particular problem from economy.
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Assessment methods and criteria
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Oral examination
The condition of the credit is the submission of a written assignment given by the lecturer during the enrollment of the subject. The successful completion of the course requires the understanding of selected concepts of mathematical and statistical methods and the ability to apply acquired knowledge in solving concrete problems of economic practice.
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Recommended literature
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Anderson, D.R. a kol. Management Science: Quantitative Approaches to Decision Making. New York : 10th ed. West Publ., 2002.
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R.H. Shumway, D.S. Stoffer. Time Series Analysis and Its Application with R Examples. Springer, 2006.
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Wooldridge, J.M. Introductory Econometrics: A Modern Approach. South-Western College pub, 2009.
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