| Course Unit Title | Course Unit Code | Type of Course Unit | Level of Course Unit | Year of Study | Semester | ECTS Credits |
|---|---|---|---|---|---|---|
| Decision Theory | MEN401 | Elective | Bachelor's degree | 4 | Fall | 5 |
Name of Lecturer(s)
Prof. Dr. Zerrin ALADAĞ
Assistant Prof. Dr. Atakan ALKAN
Learning Outcomes of the Course Unit
1) Using types of decision problems and the methods for solving these problems under uncertainty.
2) Applying types of decision problems and the methods to solving these problems under risk.
3) Using decision trees for modelling decision process.
4) Realizing decision analysis with additional information.
5) Using principles of game theory and the methods for solving these problems.
6) Using markov chains and its applications.
Program Competencies-Learning Outcomes Relation
| Program Competencies | ||||||||||||
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | ||
| Learning Outcomes | ||||||||||||
| 1 | High | High | High | No relation | Middle | No relation | No relation | No relation | High | High | Low | |
| 2 | High | High | High | No relation | Middle | No relation | No relation | No relation | High | High | Low | |
| 3 | High | High | High | No relation | Middle | No relation | No relation | No relation | High | High | Low | |
| 4 | High | High | High | No relation | Middle | No relation | No relation | No relation | High | High | Low | |
| 5 | High | High | High | No relation | Middle | No relation | No relation | No relation | High | High | Low | |
| 6 | High | High | High | No relation | Middle | No relation | No relation | No relation | High | High | Low | |
Mode of Delivery
Face to Face
Prerequisites and Co-Requisites
None
Recommended Optional Programme Components
None.
Course Contents
This course covers, introduction to decision problems, decision analysis under uncertainty, decision making under risk, decision trees, decision analysis with additional information, Game Theory (pure strategy, mixed strategy, LP model for competitive decision-making), Markov analysis and applications.
Weekly Schedule
1) Introduction to decision problems2) Introduction to decision problems
3) Decision making under uncertainty
4) Decision making under uncertainty
5) Decision making under risk
6) Decision making under risk
7) Decision Trees
8) Midterm examination/Assessment
9) Decision analysis with additional information
10) Decision analysis with additional information
11) Game theory
12) Game theory
13) Game theory
14) Markov Analysis
15) Markov Analysis
16) Final examination
Recommended or Required Reading
Planned Learning Activities and Teaching Methods
1) Lecture
2) Discussion
3) Drill and Practice
4) Problem Solving
5) Project Based Learning
Assessment Methods and Criteria
Contribution of Semester Studies to Course Grade |
40% |
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Contribution of Final Examination to Course Grade |
60% |
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Total | 100% | ||||||||||||||
Language of Instruction
Turkish
Work Placement(s)
Not Required