| Course title | State Final Exam Quantitative Methods in Economy |
|---|---|
| Course code | KMI/SZKER |
| Organizational form of instruction | no contact |
| Level of course | Master |
| Year of study | not specified |
| Semester | Winter and summer |
| Number of ECTS credits | 0 |
| Language of instruction | Czech |
| Status of course | Compulsory, Compulsory-optional |
| Form of instruction | Face-to-face |
| Work placements | This is not an internship |
| Recommended optional programme components | None |
| Lecturer(s) |
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| Course content |
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1) Probability, random variable, probability distributions. 2) Hypothesis testing -- parametric and nonparametric approaches. 3) Regression and correlation analysis - matrix approach, conditions for models, predictions. 4) Goodness of fit tests 5) Introduction to categorical data analysis, Contingency Tables and Chi-Square Test of Independence 6) Logistic regression. 7) Cluster analysis, classification, metrics, hierarchical algorithms. 8) Data visualization. 9) Utility function - ordinal and cardinal approach. Monetary utility function, construction, estimation of parameters of the function. 10) Decision making under uncertainty. Different approaches, their advantages and disadvantages. 11) Decision making under risk. Different approaches, their advantages and disadvantages. 12) Decision making with experimentation, prior and posterior probabilities, expected value of experimentation, expected value of perfect information. 13) Decision trees. 14) Portfolio optimalization, Markowitz's method, Scenario approach. 15) Basic principles of Game theory. Constant- and non-constant-sum games. 16) Oligopoly theory from a viewpoint of Game theory.
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| Learning activities and teaching methods |
| unspecified |
| Learning outcomes |
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Students know well the field of statistic methodology and decision making. They are able to recognize appropriate models from statistic methodology and decision making for their practical economic problems. Propose a solution and evaluate their results.
The aim is to get a complex view about students knowledge in the courses covering statistical methodology and decision theory applicabe during economical problem the solving. |
| Prerequisites |
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Student know statistical methodology and models for decision making. We suppose that student pass courses focused on basic statistical methodology, advanced course on data analysis (TPS,STATE or KSTAE) and Models of Decision Theory (RM2 or KRM2, MDT or KMDT).
KMI/CSTAE ----- or ----- KMI/KSTAE ----- or ----- KMI/STATE and KMI/CRM1 ----- or ----- KMI/KRM ----- or ----- KMI/RM ----- or ----- KMI/RM1 |
| Assessment methods and criteria |
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Oral examination
Students have to prove their complex understanding of the basic terminology and principles of data analysis and decision making, they have to be able to respond to particular questions and to apply theoretical knowledge in examples. |
| Recommended literature |
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| Study plans that include the course |
| Faculty | Study plan (Version) | Category of Branch/Specialization | Recommended semester | |
|---|---|---|---|---|
| Faculty: Faculty of Economics | Study plan (Version): Management and Business Economics (3) | Category: Economy | 2 | Recommended year of study:2, Recommended semester: Summer |
| Faculty: Faculty of Economics | Study plan (Version): Management and Business Economics (3) | Category: Economy | 2 | Recommended year of study:2, Recommended semester: Summer |