EMÜ661 - PROBABILITY and STATISTICS FOR ENGINEERS
| Course Name | Code | Semester | Theory (hours/week) |
Application (hours/week) |
Credit | ECTS |
|---|---|---|---|---|---|---|
| PROBABILITY and STATISTICS FOR ENGINEERS | EMÜ661 | 1st Semester | 3 | 0 | 3 | 10 |
| Prequisites | ||||||
| Course language | Turkish | |||||
| Course type | Must | |||||
| Mode of Delivery | Face-to-Face | |||||
| Learning and teaching strategies | Lecture Question and Answer Problem Solving Other: Lecture, question and answer, problem solving, individual work. | |||||
| Instructor (s) | T | |||||
| Course objective | The objective of this course is to develop students? skills to model the uncertainty/variability in engineering problems and to draw a statistical inference and use the results for decision making process. | |||||
| Learning outcomes |
| |||||
| Course Content | Probabilistic and statistical methods for engineering problems Role of statistics in engineering and data summary and presentation Univariate and multivariate probability distributions Convergence Parameter estimation Confidence intervals Hypothesis testing Goodness of fit tests. | |||||
| References | Walpole,R.E, Myers, R.H, Myers, S.L, Ye, K. Mühendisler ve Fen Bilimciler için Olasılık ve İstatistik, Dokuzuncu Baskıdan Çeviri, Çeviri Editörü: Prof.Dr. M.Akif Bakır Montgomery, D.C. and Runger, G.C. Applied Statistics and Probability for Engineers, 2010, 5th ed., Wiley. Ross, S. (2014) probability and Statistics for Engineers and Scientists, 5th ed. Elsevier. Research articles about the theory and applications of the course content | |||||
Course outline weekly
| Weeks | Topics |
|---|---|
| Week 1 | Role of statistics in engineering |
| Week 2 | Random variables and probability distributions |
| Week 3 | Mathematical expectation and discrete distributions |
| Week 4 | Discrete distributions |
| Week 5 | Continuous distributions |
| Week 6 | Midterm exam I |
| Week 7 | Continuous distributions |
| Week 8 | Moment generating function/ Sampling distribution and data definition |
| Week 9 | Statistical estimation problem |
| Week 10 | One sample and two sample estimation problem |
| Week 11 | One sample hypothesis testing |
| Week 12 | Midterm exam II |
| Week 13 | Two sample hypothesis testing |
| Week 14 | Goodness of fit tests |
| Week 15 | Study for the Final Exam |
| Week 16 | Final exam |
Assesment methods
| Course activities | Number | Percentage |
|---|---|---|
| Attendance | 0 | 0 |
| Laboratory | 0 | 0 |
| Application | 0 | 0 |
| Field activities | 0 | 0 |
| Specific practical training | 0 | 0 |
| Assignments | 5 | 15 |
| Presentation | 0 | 0 |
| Project | 0 | 0 |
| Seminar | 0 | 0 |
| Midterms | 2 | 35 |
| Final exam | 1 | 50 |
| Total | 100 | |
| Percentage of semester activities contributing grade succes | 7 | 50 |
| Percentage of final exam contributing grade succes | 1 | 50 |
| Total | 100 | |
WORKLOAD AND ECTS CALCULATION
| Activities | Number | Duration (hour) | Total Work Load |
|---|---|---|---|
| Course Duration (x14) | 14 | 3 | 42 |
| Laboratory | 0 | 0 | 0 |
| Application | 0 | 0 | 0 |
| Specific practical training | 0 | 0 | 0 |
| Field activities | 0 | 0 | 0 |
| Study Hours Out of Class (Preliminary work, reinforcement, ect) | 12 | 8 | 96 |
| Presentation / Seminar Preparation | 0 | 0 | 0 |
| Project | 0 | 0 | 0 |
| Homework assignment | 5 | 15 | 75 |
| Midterms (Study duration) | 2 | 26 | 52 |
| Final Exam (Study duration) | 1 | 35 | 35 |
| Total Workload | 34 | 87 | 300 |
Matrix Of The Course Learning Outcomes Versus Program Outcomes
| D.9. Key Learning Outcomes | Contrubition level* | ||||
|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |
| 1. Reach the necessary knowledge and methods in engineering within the scope of advanced industrial engineering studies through scientific research and evaluate knowledge and methods and implement them. | X | ||||
| 2. Implement advanced analytical methods and modeling techniques to design processes, products and systems in an innovative and original way and improve them | X | ||||
| 3. Have the competency to plan, manage and monitor processes, products and systems. | X | ||||
| 4. Evaluate the data obtained from analysis of the processes, products and systems, complete limited or missing data through scientific methods, develop data driven solution approaches. | X | ||||
| 5. Develop original methods for the efficient integration of the scarce resources such as man, machine, and material, energy, capital and time to the systems and implement these. | X | ||||
| 6. Effectively utilize computer programming languages, computer software, information and communication technology to solve problems in the field of industrial engineering. | X | ||||
| 7. Report and present advanced studies, outcomes/results and the evaluations on the design, analysis, planning, monitoring and improvement of processes, products and systems. | X | ||||
| 8. Are aware of the professional responsibility, describe the technological, economic and environmental effects of the industrial engineering applications, work as an individual independently and as a team member having an understanding of the scientific ethical values, take responsibility and lead the team. | X | ||||
| 9. Are aware of the up-to-date engineering applications, follow the necessary literature for advanced researches, have the competency to reach knowledge in a foreign language, to quote and implement them. | X | ||||
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest