Course Unit Code | Course Unit Title | Type of Course Unit | Year of Study | Semester | Number of ECTS Credits | İŞL-23-111 | | Elective | 1 | 2 | 6 |
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Level of Course Unit |
Second Cycle |
Objectives of the Course |
To provide information about different models and decision analysis techniques for making decisions under certainty and uncertainty by using concepts such as statistical decision theory, utility theory, decision trees, Bayes theorem. |
Name of Lecturer(s) |
Dr. Öğr. Üyesi Polad ALİYEV |
Learning Outcomes |
1 | 1. To know the basic concepts of statistical decision theory.;
2 . To be able to define the decision making problem.;
3. To be able to solve cost structured decision problems;
4. To know the concepts and rules of game theory.;
5. To be able to apply the analysis of decision making under uncertainty and risk.
6 . To be able to apply decision tree analysis;
7. To be able to use sample information while making statistical decisions;
8 . Using Bayes' theorem while making statistical decisions;
9 . To be able to apply Markov analysis;
10. To know the multi-criteria decision making methods.; | 2 | 1 To know the basic concepts of statistical decision theory.;
2 To be able to define the decision making problem.;
3 To be able to solve cost structured decision problems;
4 To know the concepts and rules of game theory.;
5 To be able to apply the analysis of decision making under uncertainty and risk.
6 To be able to apply decision tree analysis;
7 To be able to use sample information while making statistical decisions;
8 Using Bayes' theorem while making statistical decisions;
9 To be able to apply Markov analysis;
10 To know the multi-criteria decision making methods.; |
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Mode of Delivery |
Daytime Class |
Prerequisites and co-requisities |
none |
Recommended Optional Programme Components |
none |
Course Contents |
1 Existence of Utility Function
2. A Game and _Testing Statistical Hypotheses
3. : Properties and Expansion of Utility Function II
4. Convex Clusters I
5. Utility Function and _Statistics: Distribution Parameters
6. Decision Making Under the Uncertainty of Natural Situations I
7. The Minimax _Principle in the Uncertainty of Nature
8. Bayesian Principle in the Uncertainty of Nature
9. Admissibility and Decision-Making Principles
10. Selection of Risk Function and Decision Function
11. Postfinal Distribution and Expected Postpartum Loss
12. Parameter Estimation as a Decision-Making Problem
13. Obtaining the Bayesian Estimator with Final Losses
14. Utility Function and _Statistics: Distribution Parameters |
Weekly Detailed Course Contents |
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1 | 1. Existence of Utility Function | | | 2 | 2. A Game and _Testing Statistical Hypotheses | | | 3 | 3. Properties and Extension of Utility Function I | | | 4 | 4. Convex Clusters | | | 5 | 5. Utility Function and _Statistics: Distribution Parameters | | | 6 | 6. Decision Making Under the Uncertainty of Natural Situations I | | | 7 | 7. The Minimax _Principle in the Uncertainty of Nature | | | 8 | 8. Bayesian Principle in the Uncertainty of Nature | | | 9 | 9. Admissibility and Decision-Making Principles | | | 10 | 10. Selection of Risk Function and Decision Function | | | 11 | 11. Postfinal Distribution and Expected Postpartum Loss | | | 12 | 12. Parameter Estimation as a Decision-Making Problem | | | 13 | 13. Obtaining the Bayesian Estimator with Final Losses | | | 14 | 14. Utility Function and _Statistics: Distribution Parameters | | |
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Recommended or Required Reading |
1.James Berger, Statistical Decision Theory and Bayesian Analysis, Springer-Verlag, 1980.
2.Mustafa Aytaç, Necmi Gürsakal (editörler), Karar Verme, Dora Yayınları, 2015. |
Planned Learning Activities and Teaching Methods |
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Assessment Methods and Criteria | |
Midterm Examination | 1 | 100 | SUM | 100 | |
Final Examination | 1 | 100 | SUM | 100 | Term (or Year) Learning Activities | 40 | End Of Term (or Year) Learning Activities | 60 | SUM | 100 |
| Language of Instruction | | Work Placement(s) | none |
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Workload Calculation |
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Midterm Examination | 1 | 1 | 1 |
Final Examination | 1 | 1 | 1 |
Problem Solving | 6 | 2 | 12 |
Question-Answer | 6 | 2 | 12 |
Criticising Paper | 5 | 4 | 20 |
Individual Study for Mid term Examination | 7 | 6 | 42 |
Individual Study for Final Examination | 10 | 8 | 80 |
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Contribution of Learning Outcomes to Programme Outcomes |
LO1 | 3 | 4 | 3 | 4 | 3 | 3 | 4 | 3 | 4 | 3 | 3 | 4 | 4 | LO2 | 3 | 3 | 4 | 4 | 4 | 3 | 3 | 3 | 3 | 3 | 3 | 4 | 4 |
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* Contribution Level : 1 Very low 2 Low 3 Medium 4 High 5 Very High |
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Iğdır University, Iğdır / TURKEY • Tel (pbx): +90 476
226 13 14 • e-mail: info@igdir.edu.tr
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