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• Cover
• Preface
• Audience
• About the Book
• Course Suggestions
• The Supplemental Text Material
• Student and Instructor Supplements
• Acknowledgments
• Chapter 1: Introduction
• Problems
• Study Guide
• Readings
• 1.1 Strategy of Experimentation
• 1.2 Some Typical Applications of Experimental Design
• 1.3 Basic Principles
• 1.4 Guidelines for Designing Experiments
• 1.5 A Brief History of Statistical Design
• 1.6 Summary: Using Statistical Techniques in Experimentation
• Chapter 2: Simple Comparative Experiments
• Problems
• Study Guide
• Readings
• 2.1 Introduction
• 2.2 Basic Statistical Concepts
• 2.3 Sampling and Sampling Distributions
• 2.4 Inferences About the Differences in Means, Randomized Designs
• 2.5 Inferences About the Differences in Means, Paired Comparison Designs
• 2.6 Inferences About the Variances of Normal Distributions
• Chapter 3: Experiments with a Single Factor: The Analysis of Variance
• Problems
• Study Guide
• Readings
• 3.1 An Example
• 3.2 The Analysis of Variance
• 3.3 Analysis of the Fixed Effects Model
• 3.4 Model Adequacy Checking
• 3.5 Practical Interpretation of Results
• 3.6 Sample Computer Output
• 3.7 Determining Sample Size
• 3.8 Other Examples of Single‐Factor Experiments
• 3.9 The Random Effects Model
• 3.10 The Regression Approach to the Analysis of Variance
• 3.11 Nonparametric Methods in the Analysis of Variance
• Chapter 4: Randomized Blocks, Latin Squares, and Related Designs
• Problems
• Study Guide
• Readings
• 4.1 The Randomized Complete Block Design
• 4.2 The Latin Square Design
• 4.3 The Graeco‐Latin Square Design
• 4.4 Balanced Incomplete Block Designs
• Chapter 5: Introduction to Factorial Designs
• Problems
• Study Guide
• Readings
• 5.1 Basic Definitions and Principles
• 5.2 The Advantage of Factorials
• 5.3 The Two‐Factor Factorial Design
• 5.4 The General Factorial Design
• 5.5 Fitting Response Curves and Surfaces
• 5.6 Blocking in a Factorial Design
• Chapter 6: The 2k Factorial Design
• Problems
• Study Guide
• Readings
• 6.1 Introduction
• 6.2 The 22 Design
• 6.3 The 23 Design
• 6.4 The General 2k Design
• 6.5 A Single Replicate of the 2k Design
• 6.6 Additional Examples of Unreplicated 2k Designs
• 6.7 2k Designs are Optimal Designs
• 6.8 The Addition of Center Points to the 2k Design
• 6.9 Why We Work with Coded Design Variables
• Chapter 7: Blocking and Confounding in the 2k Factorial Design
• Problems
• Study Guide
• Readings
• 7.1 Introduction
• 7.2 Blocking a Replicated 2k Factorial Design
• 7.3 Confounding in the 2k Factorial Design
• 7.4 Confounding the 2k Factorial Design in Two Blocks
• 7.5 Another Illustration of Why Blocking Is Important
• 7.6 Confounding the 2k Factorial Design in Four Blocks
• 7.7 Confounding the 2k Factorial Design in 2p Blocks
• 7.8 Partial Confounding
• Chapter 8: Two‐Level Fractional Factorial Designs
• Problems
• Study Guide
• Readings
• 8.1 Introduction
• 8.2 The One‐Half Fraction of the 2k Design
• 8.3 The One‐Quarter Fraction of the 2k Design
• 8.4 The General 2k−p Fractional Factorial Design
• 8.5 Alias Structures in Fractional Factorials and Other Designs
• 8.6 Resolution III Designs
• 8.7 Resolution IV and V Designs
• 8.8 Supersaturated Designs
• 8.9 Summary
• Chapter 9: Additional Design and Analysis Topics for Factorial and Fractional Factorial Designs
• Problems
• Study Guide
• Readings
• 9.1 The 3k Factorial Design
• 9.2 Confounding in the 3k Factorial Design
• 9.3 Fractional Replication of the 3k Factorial Design
• 9.4 Factorials with Mixed Levels
• 9.5 Nonregular Fractional Factorial Designs
• 9.6 Constructing Factorial and Fractional Factorial Designs Using an Optimal Design Tool
• Chapter 10: Fitting Regression Models
• Problems
• Study Guide
• Readings
• 10.1 Introduction
• 10.2 Linear Regression Models
• 10.3 Estimation of the Parameters in Linear Regression Models
• 10.4 Hypothesis Testing in Multiple Regression
• 10.5 Confidence Intervals in Multiple Regression
• 10.6 Prediction of New Response Observations
• 10.7 Regression Model Diagnostics
• 10.8 Testing for Lack of Fit
• Chapter 11: Response Surface Methods and Designs
• Problems
• Study Guide
• Readings
• 11.1 Introduction to Response Surface Methodology
• 11.2 The Method of Steepest Ascent
• 11.3 Analysis of a Second‐Order Response Surface
• 11.4 Experimental Designs for Fitting Response Surfaces
• 11.5 Experiments with Computer Models
• 11.6 Mixture Experiments
• 11.7 Evolutionary Operation
• Chapter 12: Robust Parameter Design and Process Robustness Studies
• Problems
• Study Guide
• Readings
• 12.1 Introduction
• 12.2 Crossed Array Designs
• 12.3 Analysis of the Crossed Array Design
• 12.4 Combined Array Designs and the Response Model Approach
• 12.5 Choice of Designs
• Chapter 13: Experiments with Random Factors
• Problems
• Study Guide
• Readings
• 13.1 Random Effects Models
• 13.2 The Two‐Factor Factorial with Random Factors
• 13.3 The Two‐Factor Mixed Model
• 13.4 Rules for Expected Mean Squares
• 13.5 Approximate F‐Tests
• 13.6 Some Additional Topics on Estimation of Variance Components
• Chapter 14: Nested and Split‐Plot Designs
• Problems
• Study Guide
• Readings
• 14.1 The Two‐Stage Nested Design
• 14.2 The General m‐Stage Nested Design
• 14.3 Designs with Both Nested and Factorial Factors
• 14.4 The Split‐Plot Design
• 14.5 Other Variations of the Split‐Plot Design
• Chapter 15: Other Design and Analysis Topics
• Problems
• Study Guide
• Readings
• 15.1 Nonnormal Responses and Transformations
• 15.2 Unbalanced Data in a Factorial Design
• 15.3 The Analysis of Covariance
• 15.4 Repeated Measures
• Appendix
• Bibliography
• Index
• End User License Agreement