Course Syllabus

Course Information：

Year-Semester Course Number Course Name Phase Credits Hours Required/Elective Instructor Class Student NO. Withdraw Note

Fall Semester
Year 2017 232400 Experimental Designs 1 3.0 3 ★ Shu-Kai Fan GIEM 7 0 　

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Fall Semester Year 2017	232400	Experimental Designs	1	3.0	3	★	Shu-Kai Fan	GIEM	7	0

Course Plan：

Instructor Shu-Kai Fan

Email morrisfan@ntut.edu.tw

Last Updated 2017-08-23 16:08:26

Course Objective This is a first course in designing experiments and analyzing data. The course deals with the types of experiments that are frequently conducted in industrial settings. The goal is for you to learn how to plan, design, and conduct experiments efficiently and effectively, and learn how to analyze the resulting data to obtain objective conclusions. Both design and analysis issues are discussed.

Course Schedule 1. Fundamentals of engineering statistics & principles of experimentation 2. Simple comparative experiments; one-way ANOVA & CRD (completely randomized design) 3. RCBD (randomized complete block design) & Latin square designs 4. Factorial design & 2k factorial design 5. Blocking & confounding in 2k factorial design 6. 2-level fractional factorial design & its resolution; 3-level (fractional) factorial designs 7. Fitting regression model: Estimation, Diagnostics and Prediction 8. Response surface methodology & process optimization (including EVOP & Simplex EVOP) 9. Random effects model 10. Nested & split-plot designs 11. Box-Cox transformation & GLM 12. Unbalanced design (missing data) & covariance analysis of factorial design 13. Computer-generated (optimal) design theory 14. New materials from the recent literature (JQT, Technometrics, among others) Topics 12-14 are restricted by time available.

Evaluation and grading policy Assignment 20%, 3 examinations 60%, and Term Project 20%

Materials All right reserved. Do not reproduce without permission.

Foreign-language textbooks:Yes
Montgomery, D. C. (2013), Design and Analysis of Experiments, 8th Ed., Wiley. Box, G. E. P., Hunter, J. S. and Hunter, W. G. (2005), Statistics for Experimenters, 2nd Ed., Wiley.

The access to curricular consultation

Note
　

Instructor	Shu-Kai Fan
Email	morrisfan@ntut.edu.tw
Last Updated	2017-08-23 16:08:26
Course Objective	This is a first course in designing experiments and analyzing data. The course deals with the types of experiments that are frequently conducted in industrial settings. The goal is for you to learn how to plan, design, and conduct experiments efficiently and effectively, and learn how to analyze the resulting data to obtain objective conclusions. Both design and analysis issues are discussed.
Course Schedule	1. Fundamentals of engineering statistics & principles of experimentation 2. Simple comparative experiments; one-way ANOVA & CRD (completely randomized design) 3. RCBD (randomized complete block design) & Latin square designs 4. Factorial design & 2k factorial design 5. Blocking & confounding in 2k factorial design 6. 2-level fractional factorial design & its resolution; 3-level (fractional) factorial designs 7. Fitting regression model: Estimation, Diagnostics and Prediction 8. Response surface methodology & process optimization (including EVOP & Simplex EVOP) 9. Random effects model 10. Nested & split-plot designs 11. Box-Cox transformation & GLM 12. Unbalanced design (missing data) & covariance analysis of factorial design 13. Computer-generated (optimal) design theory 14. New materials from the recent literature (JQT, Technometrics, among others) Topics 12-14 are restricted by time available.
Evaluation and grading policy	Assignment 20%, 3 examinations 60%, and Term Project 20%
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:Yes Montgomery, D. C. (2013), Design and Analysis of Experiments, 8th Ed., Wiley. Box, G. E. P., Hunter, J. S. and Hunter, W. G. (2005), Statistics for Experimenters, 2nd Ed., Wiley.
The access to curricular consultation
Note