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Fundamental Concepts in the Design of Experiments (Hicks)

 
 Author(s)  Hicks, Charles R.; Turner, Kenneth V.
 Title  Fundamental Concepts in the Design of Experiments
 Edition  Fifth Edition
 Year  1999
 Publisher  Oxford University Press
 ISBN  0-19-512273-9
 Website  www.oup.com

 http://www.oup.com/us/catalog/he/subject/Engineering/GeneralEngineering/ExperimentalDesign/?view=usa&ci=9780195122732
 




Table of Contents

Preface

1.    The Experiment, the Design, and the Analysis
1.1. Introduction to Experimental Design
1.2. The Experiment
1.3. The Design
1.4. The Analysis
1.5. Examples
1.6. Summary in Outline
1.7. Further Reading

2.
    Review of Statistical Inference
2.1. Introduction
2.2. Estimation
2.3. Tests of Hypothesis
2.4. The Operating Characteristic Curve
2.5. How Large a Sample?
2.6. Application to Tests on Variances
2.7. Application to Tests on Means
2.8. Assessing Normality
2.9. Applications to Tests on Proportions
2.10. Analysis of Experiments with SAS
2.11. Further Reading

3.
    Single-Factor Experiments with No Restrictions on Randomization
3.1. Introduction
3.2. Analysis of Variance Rationale
3.3. After ANOVA--What?
3.4. Tests on Means
3.5. Confidence Limits on Means
3.6. Components of Variance
3.7. Checking the Model
3.8. SAS Programs for ANOVA and Tests after ANOVA
3.9. Summary
3.10. Further Reading

4.
    Single-Factor Experiments: Randomized Block and Latin Square Designs
4.1. Introduction
4.2. Randomized Complete Block Design
4.3. ANOVA Rationale
4.4. Missing Values
4.5. Latin Squares
4.6. Interpretations
4.7. Assessing the Model
4.8. Graeco-Latin Squares
4.9. Extensions
4.10. SAS Programs for Randomized Blocks and Latin Squares
4.11. Summary
4.12. Further Reading

5.
    Factorial Experiments
5.1. Introduction
5.2. Factorial Experiments: An Example
5.3. Interpretations
5.4. The Model and Its Assessment
5.5. ANOVA Rationale
5.6. One Observation Per Treatment
5.7. SAS Programs for Factorial Experiments
5.8. Summary
5.9. Further Reading
 
6.    Fixed, Random, and Mixed Models
6.1. Introduction
6.2. Single-Factor Models
6.3. Two-Factor Models
6.4. EMS Rules
6.5. EMS Derivations
6.6. The Pseudo-F Test
6.7. Expected Mean Squares Via Statistical Computing Packages
6.8. Remarks
6.9. Repeatability and Reproducibility for a Measurement System
6.10. SAS Problems for Random and Mixed Models
6.11. Further Reading
 
7.    Nested and Nested-Factorial Experiments
7.1. Introduction
7.2. Nested Experiments
7.3. ANOVA Rationale
7.4. Nested-Factorial Experiments
7.5. Repeated-Measures Design and Nested-Factorial Experiments
7.6. SAS Programs for Nested and Nested-Factorial Experiments
7.7. Summary
 
8.    Experiments of Two or More Factors: Restrictions on Randomization
8.1. Introduction
8.2. Factorial Experiment in a Randomized Block Design
8.3. Factorial Experiment in a Latin Square Design
8.4. Remarks
8.5. SAS Programs
8.6. Summary

9.    2f Factorial Experiments.
9.1. Introduction
9.2. 2 Squared Factorial
9.3. 2 Cubed Factorial
9.4. 2f Remarks
9.5. The Yates Method
9.6. Analysis of 2f Factorials When n=1
9.7 Some Commments about Computer Use.
9.8. Summary

10.
    3f Factorial Experiments
10.1. Introduction
10.2. 3 Squared Factorial
10.3. 3 Cubed Factorial
10.4. Computer Programs
10.5. Summary

11.
   Factorial Experiment: Split-Plot Design
11.1. Introduction
11.2. A Split-Plot Design
11.3. A Split-Split-Plot Design
11.4. Using SAS to Analyze a Split-Plot Experiment
11.5. Summary
11.6. Further Reading

12.
    Factorial Experiment: Confounding in Blocks
12.1. Introduction
12.2. Confounding Systems
12.3. Block Confounding, No Replication
12.4. Block Confounding with Replication
12.5. Confounding in 3F Factorials
12.6. SAS Progrms
12.7. Summary
12.8. Further Reading

13.
   Fractional Replication
13.1. Introduction
13.2. Aliases
13.3. 2f Fractional Replications
13.4. Plackett-Burman Designs
13.5. Design Resolution
13.6. 3f-k Fractional Factorials
13.7. SAS Programs
13.8. Summary
13.9. Further Reading

14.
    The Taguchi Approach to the Design of Experiments
14.1. Introduction
14.2. The L4 (2 Cubed) Orthogonal Array
14.3. Outer Arrays
14.4. Signal-To-Noise Ratio
14.5. The L8 (2 7) Orthogonal Array
14.6. The L16 (2 15) Orthogonal Array
14.7. The L9 (3 4) Orthogonal Array
14.8. Some Other Taguchi Designs
14.9. Summary
14.10. Further Reading

15.
    Regression
15.1. Introduction
15.2. Linear Regression
15.3. Curvilinear Regression
15.4. Orthogonal Polynomials
15.5. Multiple Regression
15.6. Summary
15.7. Further Reading

16.
Miscellaneous Topics
16.1. Introduction
16.2. Covariance Analysis
16.3. Response Surface Experimentation
16.4. Evolutionary Operation (EVOP)
16.5. Analysis of Attribute Data
16.6. Randomized Incomplete Blocks: Restriction On Experimentation
16.7. Youden Squares
16.8. Further Reading

Summary and Special Problems
Glossary of Terms
References

Statistical Tables
Table A. Areas Under the Normal Curve
Table B. Student's t Distribution
Table C. Cumulative Chi-Square Distribution
Table D. Cumulative F Distribution
Table E.1. Upper 5% of Studentized Range q
Table E.2. Upper 1% of Studentized Range q
Table F. Coefficients of Orthogonal Polynomials

Answers to Selected Problems
Index





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