Department of Statistics
H236301
Experimental Design
(實驗設計)
Fall 2010
This mission of Department of Statistics is to cultivate quality professionals with enthusiasm and
global perspectives.
Undergraduate Program Learning Goals (goals covered by this course are indicated):

1
Undergraduate students should be able to communicate effectively verbally and in writing.

2
Undergraduate students should solve strategic problems with a creative and innovative approach.
3
Undergraduate students should demonstrate leadership skills and ethics demanded of a person in authority.
4
Undergraduate students should possess a global economic and management perspective.
5
Undergraduate students should possess the necessary skills and values demanded of a true professional.

Instructor/開課教師:
Shuen-Lin Jeng /鄭順林
sljeng@stat.ncku.edu.tw
(06)2757575#53640
Office Hours: Monday 14:10-16:00 PM, Wednesday 11:10-12:00 AM, Friday 10:10-12:00
AM
Prerequisite/先修科目 :
Statistics, Regression Analysis
統計學, 回歸分析
Course Description/課程概述:
The purpose of this course is to teach students the methods of experiments in order to
obtain the required information under the constraint of cost limitation. We also will
discuss the methods of analysis for the collected data and the results of analysis for the
decision making. The practical application areas may include agriculture, biology,
medical science, dug development, information technology and all kinds of problems
which need experiments.
對於特定的問題,研究應該用如何種實驗方法才能獲得所需的資訊，並使實驗成
本最少。討論用何種分析方法歸納實驗觀測值，以下結論。
主要實際應用在農業，生物，醫學，製藥，資訊業，各種工業，以及需要用實驗
取得資訊的問題。
Course Objectives/教學目標:
Mastery in methods of design of experiment and related data analysis, including problem
solving and analytical skills; Capability of designing an appropriate experiment and to
implement the experiment under the guideline of variability control by working on a group
project ; Ability in using statistical software Minitab, SAS, and R to process the data
analysis; Strong skill of delivering logical written reports as well as clear oral
presentations.
熟練實驗設計方法與相關資料分析的各種技術以解決實際問題。經由合作的專題計
畫來完成設計實驗的訓練並在控制變因的情形下執行實驗。能夠使用統計軟體
Minitab, SAS, R 來分析實驗資料。具有成熟的技術撰寫書面報告並且能用口語清晰
的表達。
Content Summary/授課課程大綱明細:
1. Basic concept, review of statistical inference.
A. Basic Principles of DOE: randomization, replication and blocking
B. Experimental units and factorial design
C. Hypothesis testing and confidence intervals
D. Sample size determination
2. Single-factor experiments and factorial experiments.
A. Analysis of variance for single factor
B. Proof of expectation of mean squares
C. Model adequacy checking
D. Power transformation to stabilized variance
E. Contrasts and multiple comparisons
F. Nonparametric method in ANOVA
3. Experiments with blocking factors
A. Randomized complete block design
B. Latin Square design
C. Graeco-Latin Square Design
D. Balanced incomplete block design
4. Factorial Experiment
A.
B.
C.
D.
E.
The advantage of factorial design
Two factor factorial design
General factorial design
Fitting response surface
Blocking in a factorial design
5. Random effect model
A. Two factor factorial with random factors
B. Two factor mixed model
C. Rules of expected mean squares
D. Approximate F test
6. Nested-factorial and split-plot design
A. Two-stage nested design
B. M-stage nested design
C. Design with both nested and factorial factors
D. Split-plot and split-split plot design
7. Blocking and confounding systems for two level factorials
A.
B.
C.
Blocking a replicated 2^k factorial design
Confounding in a replicated 2^k factorial design
Confounding the replicated 2^k factorial design with 2 and 4 blocks
D. Partial confounding
8. Two-level fractional factorial design
A. One half fraction of the 2^k design
B. One quarter fraction of the 2^k design
C. Alias structures
D. Resolution III, IV, V designs
E. Supersaturated designs
9. Other topics in factorial and fractional factorial design
A. The 3^k factorial design
B. Confounding in 3^k factorial design
C. Fractional replication of the 3^k factorial design
D. Fractional in the mixed levels
10. Response surface experimentation.
A. Method of steepest ascent
B. Analysis of second order response surface
C. Experimental design for fitting response surface
D. Experiment for computer design
11. Robust design
A. Cross array design
B. Analysis of cross array design
C. Combine array design with the response model approach
D. Choice of design
12. Many real examples will be given and a project will due at the end of the semester.
Minitab,SAS, and R will be used for the class.
Textbook/教材課本:
1. Design and Analysis of Experiments. By D. C. Montgomery. Seventh Edition.
2009, John Wiley and Sons.
Recommended references/參考書目:
1. Experiments. By Wu and Hamada. Second edition. 2009, John Wiley and Sons.
2. Statistics for Experimenters. By Box, Hunter and Hunter. Second Edition. 2005.
John Wiley and Sons.
3. Fundamental Concepts in the Design of Experiments. By C. R. Hicks and K. V.
Turner, Jr. Fifth Edition. 1999, Oxford. (歐亞)
Course Requirement/課程要求:
Homework, Project and Oral Report, Midterm and Final Exam.
Grading Policy for AACSB Multiple Assessment:
Home
Midterms
Work
25%
15%
 Oral Commu./ Presentation
COMMU
 Written Communication
20%
20%
 Creativity and Innovation
 Problem Solving
30%
40%
CPSI
30%
40%
 Analytical Skills
LEAD
Leadership & Ethic
 Social responsibility
GLOB
 Global Awareness
VSP
 Values, Skills & Profess.
 Information Technology
 Management Skills
20%
Project
25%
30%
10%
20%
10%
10%
20%
Final
30%
Class
Performance
5%
40%
20%
30%
40%
40%
30%