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| Course Description |
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| Course Name |
: |
Risk Theory |
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| Course Code |
: |
ISB-563 |
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| Course Type |
: |
Optional |
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| Level of Course |
: |
Second Cycle |
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| Year of Study |
: |
1 |
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| Course Semester |
: |
Fall (16 Weeks) |
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| ECTS |
: |
6 |
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| Name of Lecturer(s) |
: |
Assoc.Prof.Dr. DENİZ ÜNAL
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| Learning Outcomes of the Course |
: |
Know the risk notations and risk information
Classify the risk models
Define the risk by using the distribution
Know the individual risk models
Know the Birnbaum ve Barlow-Proshan index
Know the collective risk models
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|
| Mode of Delivery |
: |
Face-to-Face |
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| Prerequisites and Co-Prerequisites |
: |
None |
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| Recommended Optional Programme Components |
: |
None |
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| Aim(s) of Course |
: |
This course aims to provide the students with the knowledge of risk notations, risk measure, classification of risk models, risk density and hazard rates, constructive reliability, collective risk models. |
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| Course Contents |
: |
Risk notations, Risk measure, Classification of risk models, Risk density and hazard rates, Constructive reliability, Collective risk models |
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| Language of Instruction |
: |
Turkish |
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| Work Place |
: |
Seminar room of the department |
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Course Outline /Schedule (Weekly) Planned Learning Activities |
| Week | Subject | Student's Preliminary Work | Learning Activities and Teaching Methods |
|
1 |
Risk notations |
Searching, reading the source |
Lecture, discussion, project, paper, research |
|
2 |
Risk measure |
Searching, reading the source |
Lecture, discussion, project, paper, research |
|
3 |
Classification of risk models |
Searching, reading the source |
Lecture, discussion, project, paper, research |
|
4 |
Risk distributions |
Searching, reading the source |
Lecture, discussion, project, paper, research |
|
5 |
Risk density and hazard rates |
Searching, reading the source |
Lecture, discussion, project, paper, research |
|
6 |
Individual risk models |
Searching, reading the source |
Lecture, discussion, project, paper, research |
|
7 |
Risk construction |
Searching, reading the source |
Lecture, discussion, project, paper, research |
|
8 |
Mid-term exam |
reading the source |
Mid term exam |
|
9 |
Constructive reliability |
Searching, reading the source |
Lecture, discussion, project, paper, research |
|
10 |
Birnbaum ve Barlow-Proshan index |
Searching, reading the source |
Lecture, discussion, project, paper, research |
|
11 |
Collective risk models |
Searching, reading the source |
Lecture, discussion, project, paper, research |
|
12 |
Increment probability, Risk theory in insurance |
Searching, reading the source |
Lecture, discussion, project, paper, research |
|
13 |
Sparre Andersen Model |
Searching, reading the source |
Lecture, discussion, project, paper, research |
|
14 |
Sparre Andersen Model |
Searching, reading the source |
Lecture, discussion, project, paper, research |
|
15 |
Presentations |
Presentations |
Presentations |
|
16/17 |
Final Exam |
reading the source |
Writing exam |
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Required Course Resources |
| Resource Type | Resource Name |
| Recommended Course Material(s) |
 Elements of General Risk Theory, Rykov, V.
Matlab ile risk yönetimi, Uzunoğlu, M., Geçer, t., Eren, K. Kızıl,A., Onar, Ö.Ç.
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| |
| Required Course Material(s) | |
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Assessment Methods and Assessment Criteria |
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Semester/Year Assessments |
Number |
Contribution Percentage |
|
Mid-term Exams (Written, Oral, etc.) |
1 |
90 |
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Homeworks/Projects/Others |
4 |
10 |
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Total |
100 |
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Rate of Semester/Year Assessments to Success |
40 |
| |
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Final Assessments
|
100 |
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Rate of Final Assessments to Success
|
60 |
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Total |
100 |
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| Contribution of the Course to Key Learning Outcomes |
| # | Key Learning Outcome | Contribution* |
|
1 |
Possess advanced level of theoretical and applicable knowledge in the field of Probability and Statistics. |
5 |
|
2 |
Conduct scientific research on Mathematics, Probability and Statistics. |
5 |
|
3 |
Possess information, skills and competencies necessary to pursue a PhD degree in the field of Statistics. |
5 |
|
4 |
Possess comprehensive information on the analysis and modeling methods used in Statistics. |
0 |
|
5 |
Present the methods used in analysis and modeling in the field of Statistics. |
0 |
|
6 |
Discuss the problems in the field of Statistics. |
4 |
|
7 |
Implement innovative methods for resolving problems in the field of Statistics. |
3 |
|
8 |
Develop analytical modeling and experimental research designs to implement solutions. |
0 |
|
9 |
Gather data in order to complete a research. |
3 |
|
10 |
Develop approaches for solving complex problems by taking responsibility. |
0 |
|
11 |
Take responsibility with self-confidence. |
4 |
|
12 |
Have the awareness of new and emerging applications in the profession |
5 |
|
13 |
Present the results of their studies at national and international environments clearly in oral or written form. |
0 |
|
14 |
Oversee the scientific and ethical values during data collection, analysis, interpretation and announcment of the findings. |
0 |
|
15 |
Update his/her knowledge and skills in statistics and related fields continously |
0 |
|
16 |
Communicate effectively in oral and written form both in Turkish and English. |
0 |
|
17 |
Use hardware and software required for statistical applications. |
0 |
| * Contribution levels are between 0 (not) and 5 (maximum). |
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| Student Workload - ECTS |
| Works | Number | Time (Hour) | Total Workload (Hour) |
| Course Related Works |
|
Class Time (Exam weeks are excluded) |
14 |
3 |
42 |
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Out of Class Study (Preliminary Work, Practice) |
14 |
3 |
42 |
| Assesment Related Works |
|
Homeworks, Projects, Others |
4 |
8 |
32 |
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Mid-term Exams (Written, Oral, etc.) |
1 |
15 |
15 |
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Final Exam |
1 |
20 |
20 |
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Total Workload: | 151 |
| Total Workload / 25 (h): | 6.04 |
| ECTS Credit: | 6 |
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