| Course Name | Statistical Decision Theory |
| Code | Semester | Theory (hour/week) | Application/Lab (hour/week) | Local Credits | ECTS |
|---|---|---|---|---|---|
| STAT 563 | Fall/Spring | 3 | 0 | 3 | 7.5 |
| Prerequisites | None | |||||
| Course Language | English | |||||
| Course Type | Elective | |||||
| Course Level | Second Cycle | |||||
| Mode of Delivery | - | |||||
| Teaching Methods and Techniques of the Course | ||||||
| Course Coordinator | - | |||||
| Course Lecturer(s) | ||||||
| Assistant(s) | - | |||||
| Course Objectives | The aim of this course is to give an overview of fundamental ideas and results about statistical decision making procedures. |
| Learning Outcomes | The students who succeeded in this course;
|
| Course Description | The topics covered in this course include elements of decision theory, risk, estimation and hypothesis testing in a setup of decision theory, Bayes risk and decision, and optimal stopping rules. |
| Related Sustainable Development Goals | |
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| Core Courses | |
| Major Area Courses | ||
| Supportive Courses | ||
| Media and Managment Skills Courses | ||
| Transferable Skill Courses |
| Week | Subjects | Required Materials |
| 1 | Statistical modeling: The need for Statistics | “Statistical Decision Theory and Bayesian Analysis” by James O. Berger, Springer. |
| 2 | Statistical modeling: Basic concepts and elements | “Statistical Decision Theory and Bayesian Analysis” by James O. Berger, Springer. |
| 3 | Statistical modeling: Inference | “Statistical Decision Theory and Bayesian Analysis” by James O. Berger, Springer. |
| 4 | Basic elements of statistical decision theory: | “Statistical Decision Theory and Bayesian Analysis” by James O. Berger, Springer. |
| 5 | Expected loss, Decision rules, and Risk | “Statistical Decision Theory and Bayesian Analysis” by James O. Berger, Springer. |
| 6 | Decision principles | “Statistical Decision Theory and Bayesian Analysis” by James O. Berger, Springer. |
| 7 | Utility and Loss: Utility Theory | “Statistical Decision Theory and Bayesian Analysis” by James O. Berger, Springer. |
| 8 | Utility and Loss: The Utility of Money, The loss function | “Statistical Decision Theory and Bayesian Analysis” by James O. Berger, Springer. |
| 9 | Prior information and subjective probability | “Statistical Decision Theory and Bayesian Analysis” by James O. Berger, Springer. |
| 10 | Prior information and subjective probability | “Statistical Decision Theory and Bayesian Analysis” by James O. Berger, Springer. |
| 11 | Bayesian Analysis | “Statistical Decision Theory and Bayesian Analysis” by James O. Berger, Springer. |
| 12 | Bayesian Analysis | “Statistical Decision Theory and Bayesian Analysis” by James O. Berger, Springer. |
| 13 | Minimax Analysis | “Statistical Decision Theory and Bayesian Analysis” by James O. Berger, Springer. |
| 14 | Minimax Analysis | “Statistical Decision Theory and Bayesian Analysis” by James O. Berger, Springer. |
| 15 | Applications | “Statistical Decision Theory and Bayesian Analysis” by James O. Berger, Springer. |
| 16 | Review of the Semester |
| Course Notes/Textbooks | “Statistical Decision Theory and Bayesian Analysis” by James O. Berger, Springer. |
| Suggested Readings/Materials | “Applied Statistical Decision Theory” by H. Raiffa and R. Schlaifer.“Statistical Inference” by George Casella and Roger L. Berger. |
| Semester Activities | Number | Weigthing |
| Participation | ||
| Laboratory / Application | ||
| Field Work | ||
| Quizzes / Studio Critiques | ||
| Portfolio | ||
| Homework / Assignments | ||
| Presentation / Jury | 1 | 10 |
| Project | 1 | 20 |
| Seminar / Workshop | ||
| Oral Exam | ||
| Midterm | 1 | 30 |
| Final Exam | 1 | 40 |
| Total |
| Weighting of Semester Activities on the Final Grade | 3 | 60 |
| Weighting of End-of-Semester Activities on the Final Grade | 1 | 40 |
| Total |
| Semester Activities | Number | Duration (Hours) | Workload |
|---|---|---|---|
| Course Hours (Including exam week: 16 x total hours) | 16 | 3 | 48 |
| Laboratory / Application Hours (Including exam week: 16 x total hours) | 16 | ||
| Study Hours Out of Class | 15 | 6 | 90 |
| Field Work | |||
| Quizzes / Studio Critiques | |||
| Portfolio | |||
| Homework / Assignments | |||
| Presentation / Jury | 1 | 5 | |
| Project | 1 | 17 | |
| Seminar / Workshop | |||
| Oral Exam | |||
| Midterms | 1 | 25 | |
| Final Exams | 1 | 40 | |
| Total | 225 |
| # | Program Competencies/Outcomes | * Contribution Level | ||||
1 | 2 | 3 | 4 | 5 | ||
| 1 | To have an appropriate knowledge of methodological and practical elements of the basic sciences and to be able to apply this knowledge in order to describe engineering-related problems in the context of industrial systems. | |||||
| 2 | To be able to identify, formulate and solve Industrial Engineering-related problems by using state-of-the-art methods, techniques and equipment. | |||||
| 3 | To be able to use techniques and tools for analyzing and designing industrial systems with a commitment to quality. | |||||
| 4 | To be able to conduct basic research and write and publish articles in related conferences and journals. | |||||
| 5 | To be able to carry out tests to measure the performance of industrial systems, analyze and interpret the subsequent results. | |||||
| 6 | To be able to manage decision-making processes in industrial systems. | |||||
| 7 | To have an aptitude for life-long learning; to be aware of new and upcoming applications in the field and to be able to learn them whenever necessary. | |||||
| 8 | To have the scientific and ethical values within the society in the collection, interpretation, dissemination, containment and use of the necessary technologies related to Industrial Engineering. | |||||
| 9 | To be able to design and implement studies based on theory, experiments and modeling; to be able to analyze and resolve the complex problems that arise in this process; to be able to prepare an original thesis that comply with Industrial Engineering criteria. | |||||
| 10 | To be able to follow information about Industrial Engineering in a foreign language; to be able to present the process and the results of his/her studies in national and international venues systematically, clearly and in written or oral form. | |||||
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest
