Undergraduate
Faculty of Engineering and Architecture
Civil Engineering
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Design of Experiments

Course CodeSemester Course Name LE/RC/LA Course Type Language of Instruction ECTS
CE0846 Design of Experiments 2/2/0 DE English 4
Course Goals
 To raise awareness of students about digital applications in different departments.
Prerequisite(s) -
Corequisite(s) -
Special Requisite(s) -
Instructor(s) -
Course Assistant(s) -
Schedule The course is not opened for this semester.
Office Hour(s) The course is not opened for this semester.
Teaching Methods and Techniques Lecture, discussion
Principle Sources Lecture notes and presentations
Other Sources -
Course Schedules
Week Contents Learning Methods
1. Week Introduction Oral Presentation
2. Week Simple Linear Regression Model (SLR) Oral Presentation
3. Week Simple Linear Regression Model (SLR) Oral Presentation
4. Week Residual Analysis Oral Presentation
5. Week Multiple Linear Regression Model (MLR) Oral Presentation
6. Week Model Building in MLR Oral Presentation
7. Week Single Factor Analysis of Variance (ANOVA) Model Oral Presentation
8. Week Midterm Exam Exam
9. Week Two Factor ANOVA and General Linear Model Oral Presentation
10. Week Full Factorial Experiments Oral Presentation
11. Week Introduction to full factorial 2^k designs Oral Presentation
12. Week Full factorial 2^k designs Oral Presentation
13. Week Fractional factorial designs Oral Presentation
14. Week Fractional factorial designs Oral Presentation
15. Week
16. Week
17. Week
Assessments
Evaluation tools Quantity Weight(%)
Midterm(s) 1 40
Final Exam 1 60


Program Outcomes
PO-1Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledge in these areas in the solution of complex engineering problems.
PO-2Ability to formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose.
PO-3Ability to design a complex systemi process, device or product under realistic constraints and conditions, in such a way as to meet the desired results; ability to apply modern design methods for this purpose.
PO-4Ability to select and use modern techniques and tools needed for analyzing and Solving complex problems encountered in engineering practice; ability to employ information technologies effectively.
PO-5Ability to design and conduct experiments, gather data, analyze and interpret results for investing complex engineering problems or discipline specific research questions.
PO-6Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
PO-7Ability to communicate effectivley, both orally and in writing; knowledge of a minimum of one foreign language; ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instruction.
PO-8Awareness of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.
PO-9Knowledge on behavior according ethical principles, professional and ethical responsibility and standards used in engineering practices.
PO-10Knowledge about business life practices such as project management, risk management, and change management; awareness in entrepreneurship, innovation; knowledge about sustainable development.
PO-11Knowledge about the global and social effects of engineering practices on health, environment, and safety, and contemporary issues of the century reflected into the field of engineering; awareness of the legal consequences of engineering solutions.
Learning Outcomes
LO-1Applies Simple Linear Regression Model (SLR) by hand, applies Multiple Linear Regression (MLR) by using Excel and MINITAB.
LO-2Writes down the Hypothesis to check the significance of independent variables and the model, distinguish between t- test and F- test, performs the tests, ranks the variables based on their significance in the model and interprets the test results in the problem context. Costructs scatter plot and probability plot and interprets them.
LO-3Designs and conducts factorial experiments, constructs and/or completes ANOVA table for a given problem, performs t-test and F-test, calculates the P- value for the tests, interprets the results of the tests, and ranks the variables based on their level of significance.
LO-4Uses graphical plots such as main effects plot, interaction plot, the normal probability plot to analyze the 2k experiments and interprets them.
LO-5Uses Confounding technique when it is necessary, assesses the design resolution, designs blocks to confound a given effect and analyses results of the experiment.
Course Assessment Matrix:
Program Outcomes - Learning Outcomes Matrix
 PO 1PO 2PO 3PO 4PO 5PO 6PO 7PO 8PO 9PO 10PO 11
LO 1
LO 2
LO 3
LO 4
LO 5