Basic design for scientific and industrial experiments: single-factor, and multiple-factor, completely randomized designs, randomized blocks, incomplete blocks, orthogonal contrasts, general regression approach, Latin squares, response surfaces and optimization, use of statistical packages (MINITAB and Excel).
Prerequisite(s)
IE4102 Statistics for Engineers
Corequisite(s)
None
Special Requisite(s)
The minimum qualifications that are expected from the students who want to attend the course (Examples: Foreign language level, attendance, known theoretical
pre-qualifications, etc.)
-Lecture, question-answer, discussion, problem solving
Principle Sources
-Douglas C. Montgomery and George C. Runger (2010). Applied Statistics and Probability for Engineers, 6th edition. Wiley.
Other Sources
-Douglas C. Montgomery (2013). Design and Analysis of Experiments, 8th edition. Wiley.
Course Schedules
Week
Contents
Learning Methods
1. Week
Introduction
Lecture, question-answer, discussion, problem solving
2. Week
Simple Linear Regression Model (SLR)
Lecture, question-answer, discussion, problem solving
3. Week
Simple Linear Regression Model (SLR)(Con’t)
Lecture, question-answer, discussion, problem solving
4. Week
Residual Analysis
Lecture, question-answer, discussion, problem solving
5. Week
Multiple Linear Regression Model (MLR)
Lecture, question-answer, discussion, problem solving
6. Week
Model Building in MLR
Lecture, question-answer, discussion, problem solving
7. Week
Single Factor Analysis of Variance (ANOVA) Model
Lecture, question-answer, discussion, problem solving
8. Week
MIDTERM
Lecture, question-answer, discussion, problem solving
9. Week
Two Factor ANOVA and General Linear Model
10. Week
Full Factorial Experiments
Lecture, question-answer, discussion, problem solving
11. Week
Introduction to full factorial 2^k designs
Lecture, question-answer, discussion, problem solving
12. Week
Full factorial 2^k designs (Con’t)
Lecture, question-answer, discussion, problem solving
13. Week
Fractional factorial designs
Lecture, question-answer, discussion, problem solving
14. Week
Project Presentations
Project Presentations
15. Week
Final
16. Week
Final
17. Week
Final
Assessments
Evaluation tools
Quantity
Weight(%)
Midterm(s)
1
24
Quizzes
4
16
Project(s)
1
20
Final Exam
1
40
Program Outcomes
PO-1
Ability to apply theoretical and practical knowledge gained by Mathematics, Science and their engineering fields and ability to use their knowledge in solving complex engineering problems.
PO-2
Ability of determining, defining, formulating and solving complex engineering problems; for that purpose develop the ability of selecting and implementing suitable models and methods of analysis.
PO-3
Ability of designing a complex system, process, device or product under real world constraints and conditions serving certain needs; for this purpose ability of applying modern design techniques
PO-4
Ability of selecting and using the modern techniques and devices which are necessary for analyzing and solving complex problems in engineering implementations; ability of efficient usage of information technologies.
PO-5
Ability of designing experiments, conducting tests, collecting data and analyzing and interpreting the solutions to investigate of complex engineering problems or discipline-specific research topics.
PO-6
Ability of working efficiently in intra-disciplinary and multi-disciplinary teams; individual working ability and habits.
PO-7
Ability of verbal and written communication skills; and at least one foreign language skills, ability to write effective reports and understand written reports, ability to prepare design and production reports, ability to make impressive presentation, ability to give and receive clear and understandable instructions
PO-8
Awareness of importance of lifelong learning; ability to access data, to follow up the recent innovation in science and technology for continuous self-improvement.
PO-9
Conformity to ethical principles; knowledge about occupational and ethical responsibility, and standards used in engineering applications.
PO-10
Knowledge about work life implementations such as project management, risk management and change management; awareness about entrepreneurship and innovativeness; knowledge about sustainable development.
PO-11
Knowledge about effects of engineering applications on health, environment and security in global and social dimensions, and on the problems of the modern age in engineering; awareness about legal outcomes of engineering solutions.
Learning Outcomes
LO-1
Applies Simple Linear Regression Model (SLR) by hand, applies Multiple Linear Regression (MLR) by using Excel and MINITAB.
LO-2
Writes 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-3
Designs 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-4
Calculates the factor effects in a 2^k full factorial design, constructs and/or completes an ANOVA table manually or by using Excel and MINITAB, and explains the findings of the analysis in the problem context.
LO-5
Uses graphical plots such as main effects plot, interaction plot, the normal probability plot to analyze the 2k experiments and interprets them.
LO-6
Uses Confounding technique when it is necessary, assesses the design resolution, designs blocks to confound a given effect and analyses results of the experiment.
