GRADUATE SCHOOL
M.SC. in Computer Engineering (Without Thesis)
IE 544 | Course Introduction and Application Information
| Course Name |
Experimental Design in Engineering
|
|
Code
|
Semester
|
Theory
(hour/week) |
Application/Lab
(hour/week) |
Local Credits
|
ECTS
|
|
IE 544
|
Fall/Spring
|
3
|
0
|
3
|
7.5
|
| Prerequisites |
None
|
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| Course Language |
English
|
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| Course Type |
Elective
|
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| Course Level |
Second Cycle
|
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| Mode of Delivery | - | |||||
| Teaching Methods and Techniques of the Course | - | |||||
| Course Coordinator | ||||||
| Course Lecturer(s) | ||||||
| Assistant(s) | - | |||||
| Course Objectives | To teach general statistical analysis, design of engineering experiments and projects using theory of least squares, analysis of variance, randomized blocks, factorial experiments, and associated topics as well as engineering experimental design and analysis using software packages. |
| Learning Outcomes |
The students who succeeded in this course;
|
| Course Description | This course covers: basic statistical concepts; design of experiments methodology; simple comparative experiments; single and multi-factor experiments; randomized blocks; Latin square designs; full factorial designs; fractional factorial designs; regression models; response surface methodology. |
|
|
Core Courses | |
| Major Area Courses | ||
| Supportive Courses | ||
| Media and Management Skills Courses | ||
| Transferable Skill Courses |
WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES
| Week | Subjects | Related Preparation |
| 1 | Introduction | Textbook, Chapter 1 |
| 2 | Simple Comparative Experiments | Textbook, Chapter 2 |
| 3 | Experiments with a Single Factor: The Analysis of Variance | Textbook, Chapter 2 |
| 4 | Experiments with a Single Factor: The Analysis of Variance | Textbook, Chapter 2 |
| 5 | Randomized Blocks, Latin Squares, and Related Designs | Textbook, Chapter 2 |
| 6 | Introduction to Factorial Designs | Textbook, Chapter 4 |
| 7 | Midterm | Textbook, Chapter 4 |
| 8 | The 2k Factorial Design | Textbook, Chapter 4 |
| 9 | The 2k Factorial Design | Textbook, Chapter 5 |
| 10 | Blocking and Confounding in the 2k Factorial Design | Textbook, Chapter 5 |
| 11 | Two-level Fractional Factorial Designs | Textbook, Chapter 6 |
| 12 | Three-Level and Mixed-Level Factorial Designs | Textbook, Chapter 6 |
| 13 | Fitting Regression Models | Textbook, Chapter 7 |
| 14 | Fitting Regression Models | Textbook, Chapter 7 |
| 15 | Response Surface Methods and Designs | Textbook, Chapter 8 |
| 16 | Review of the Semester | Textbook, Chapter 8 |
| Course Notes/Textbooks | Douglas C. Montgomery, 2009. Design and Analysis of Experiments, 7th Ed., John Wiley & Sons, Inc., NJ, USA. |
| Suggested Readings/Materials | Course notes and Slayts |
EVALUATION SYSTEM
| Semester Activities | Number | Weigthing |
| Participation | ||
| Laboratory / Application |
2
|
20
|
| Field Work | ||
| Quizzes / Studio Critiques | ||
| Portfolio | ||
| Homework / Assignments |
3
|
15
|
| Presentation / Jury | ||
| Project | ||
| Seminar / Workshop | ||
| Oral Exams | ||
| Midterm |
1
|
30
|
| Final Exam |
1
|
35
|
| Total |
| Weighting of Semester Activities on the Final Grade |
65
|
|
| Weighting of End-of-Semester Activities on the Final Grade |
35
|
|
| Total |
ECTS / WORKLOAD TABLE
| Semester Activities | Number | Duration (Hours) | Workload |
|---|---|---|---|
| Theoretical Course Hours (Including exam week: 16 x total hours) |
16
|
3
|
48
|
| Laboratory / Application Hours (Including exam week: '.16.' x total hours) |
16
|
1
|
16
|
| Study Hours Out of Class |
15
|
5
|
75
|
| Field Work |
0
|
||
| Quizzes / Studio Critiques |
0
|
||
| Portfolio |
0
|
||
| Homework / Assignments |
5
|
5
|
25
|
| Presentation / Jury |
0
|
||
| Project |
1
|
-
|
0
|
| Seminar / Workshop |
0
|
||
| Oral Exam |
0
|
||
| Midterms |
1
|
21
|
21
|
| Final Exam |
1
|
50
|
50
|
| Total |
235
|
COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP
|
#
|
Program Competencies/Outcomes |
* Contribution Level
|
||||
|
1
|
2
|
3
|
4
|
5
|
||
| 1 | Accesses information in breadth and depth by conducting scientific research in Computer Engineering, evaluates, interprets and applies information. | X | ||||
| 2 | Is well-informed about contemporary techniques and methods used in Computer Engineering and their limitations. | X | ||||
| 3 | Uses scientific methods to complete and apply information from uncertain, limited or incomplete data, can combine and use information from different disciplines. | X | ||||
| 4 | Is informed about new and upcoming applications in the field and learns them whenever necessary. | X | ||||
| 5 | Defines and formulates problems related to Computer Engineering, develops methods to solve them and uses progressive methods in solutions. | X | ||||
| 6 | Develops novel and/or original methods, designs complex systems or processes and develops progressive/alternative solutions in designs. | X | ||||
| 7 | Designs and implements studies based on theory, experiments and modelling, analyses and resolves the complex problems that arise in this process. | X | ||||
| 8 | Can work effectively in interdisciplinary teams as well as teams of the same discipline, can lead such teams and can develop approaches for resolving complex situations, can work independently and takes responsibility. | X | ||||
| 9 | Engages in written and oral communication at least in Level B2 of the European Language Portfolio Global Scale. | X | ||||
| 10 | Communicates the process and the results of his/her studies in national and international venues systematically, clearly and in written or oral form. | X | ||||
| 11 | Is knowledgeable about the social, environmental, health, security and law implications of Computer Engineering applications, knows their project management and business applications, and is aware of their limitations in Computer Engineering applications. | X | ||||
| 12 | Highly regards scientific and ethical values in data collection, interpretation, communication and in every professional activity. | X | ||||
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest