Solutions Manual for Fundamental Concepts in the Design of Experiments

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
Problems
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
Problems
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
Problems
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
Problems
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
Problems
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
Problems
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
Further Reading
Problems
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
Problems
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
9.9: Further Reading
Problems
10.: 3f Factorial Experiments
10.1: Introduction
10.2: 3 Squared Factorial
10.3: 3 Cubed Factorial
10.4: Computer Programs
10.5: Summary
Problems
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
Problems
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
Problems
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
Problems
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
Problems
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
Problems
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
Problems
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