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| Course Description |
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| Course Name |
: |
Statistical Reliability Analysis |
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| Course Code |
: |
İSB492 |
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| Course Type |
: |
Optional |
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| Level of Course |
: |
First Cycle |
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| Year of Study |
: |
4 |
|
| Course Semester |
: |
Spring (16 Weeks) |
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| ECTS |
: |
5 |
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| Name of Lecturer(s) |
: |
Assoc.Prof.Dr. GÜZİN YÜKSEL
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| Learning Outcomes of the Course |
: |
Calculates the hazard ratio estimate.
Knows the probability plotting techniques
Makes the estimation of reliability for different systems.
Learns basic reliability models
Knows the basic concepts of reliability.
Knows estimation based on life distributions
Solves problems related to reliability
Uses Life-table method
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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 |
: |
The aim of this course is to introduce reliability concept to students.Reliability estimation for different systems, reliability growth models will be given. |
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| Course Contents |
: |
Reliability estimation for different systems,Hazard rate estimation,Estimation based on life distributions,Exponential distribution,Weibull distribution,Gamma distribution,Testing based on life distributions,Determination of hazard rate for censored data,Reliability growth models,Probability plotting techniques,Hollander-Proschan test,Deshpande tests,Accelerated life testing. |
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| Language of Instruction |
: |
Turkish |
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| Work Place |
: |
Faculty of Arts and Sciences Annex Classrooms |
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Course Outline /Schedule (Weekly) Planned Learning Activities |
| Week | Subject | Student's Preliminary Work | Learning Activities and Teaching Methods |
|
1 |
Reliability estimation for different systems |
Reading related books |
Face to face description method |
|
2 |
Hazard rate estimation |
Reading related books |
Face to face description method |
|
3 |
Estimation based on life distributions |
Reading related books |
Face to face description method,solving problem on board |
|
4 |
Exponential distribution |
Reading related books |
Face to face description method,solving problem on board |
|
5 |
Weibull distribution |
Reading related books |
Face to face description method,solving problem on board |
|
6 |
Gamma distribution |
Reading related books |
Face to face description method,solving problem on board |
|
7 |
Applications |
Reading related books |
Solving problem on board,discussion |
|
8 |
Mid-term exam |
Review the topics discussed in the lecture notes |
Written exam |
|
9 |
Normal distribution, lognormal distribution. |
Reading related books |
Face to face description method,solving problem on board |
|
10 |
The reliability of the systems, the serial configuration, the parallel configuration, |
Reading related books |
Face to face description method,solving problem on board |
|
11 |
Applications to life analysis, exponential model in life analysis |
Reading related books |
Face to face description method,solving problem on board |
|
12 |
Weibull model in Life analysis |
Reading related books |
Face to face description method,solving problem on board |
|
13 |
Life table, Kaplan-Meier and Cox regression analysis |
Reading related books |
Face to face description method,solving problem on board |
|
14 |
Comparison of life curves. |
Reading related books |
Face to face description method,solving problem on board |
|
15 |
Testing based on life distributions |
Reading related books |
Face to face description method,solving problem on board |
|
16/17 |
Final Exam |
Review the topics discussed in the lecture notes |
Written exam |
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|
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Required Course Resources |
| Resource Type | Resource Name |
| Recommended Course Material(s) |
 An introduction to Reliability and Maintainability Engineering, Charles E. Ebeling McGRAW-Hill Comp, 1997.
Miller and Freund´s Probability and Statistics for Engineers, R. Johnson, Pearson Prentice Hall, 2005.
Modern Applied Biostatistical Methods Using S-Plus, S. Selvin, Oxford University Press, 1998.
Biyoistatistik, M. Şenocak, İstanbul Üniv. Yayınları, 1997.
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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 |
80 |
|
Homeworks/Projects/Others |
2 |
20 |
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Total |
100 |
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Rate of Semester/Year Assessments to Success |
40 |
| |
|
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 |
Utilize computer systems and softwares |
1 |
|
2 |
Apply the statistical analyze methods |
2 |
|
3 |
Make statistical inference(estimation, hypothesis tests etc.) |
2 |
|
4 |
Generate solutions for the problems in other disciplines by using statistical techniques |
4 |
|
5 |
Discover the visual, database and web programming techniques and posses the ability of writing programme |
0 |
|
6 |
Construct a model and analyze it by using statistical packages |
0 |
|
7 |
Distinguish the difference between the statistical methods |
2 |
|
8 |
Be aware of the interaction between the disciplines related to statistics |
4 |
|
9 |
Make oral and visual presentation for the results of statistical methods |
1 |
|
10 |
Have capability on effective and productive work in a group and individually |
3 |
|
11 |
Develop scientific and ethical values in the fields of statistics-and scientific data collection |
4 |
|
12 |
Explain the essence fundamentals and concepts in the field of Probability, Statistics and Mathematics |
5 |
|
13 |
Emphasize the importance of Statistics in life |
5 |
|
14 |
Define basic principles and concepts in the field of Law and Economics |
0 |
|
15 |
Produce numeric and statistical solutions in order to overcome the problems |
4 |
|
16 |
Construct the model, solve and interpret the results by using mathematical and statistical tehniques for the problems that include random events |
3 |
|
17 |
Use proper methods and techniques to gather and/or to arrange the data |
1 |
|
18 |
Professional development in accordance with their interests and abilities, as well as the scientific, cultural, artistic and social fields, constantly improve themselves by identifying training needs |
1 |
| * 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 |
2 |
3 |
6 |
|
Mid-term Exams (Written, Oral, etc.) |
1 |
15 |
15 |
|
Final Exam |
1 |
25 |
25 |
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Total Workload: | 130 |
| Total Workload / 25 (h): | 5.2 |
| ECTS Credit: | 5 |
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