Efnisyfirlit

• Cover
• Title Page
• Preface
  • Audience
  • About the Book
  • Course Suggestions
  • The Supplemental Text Material
  • Website
  • Acknowledgments
• CHAPTER 1: Introduction
  • 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
  • 1.7 Problems
• CHAPTER 2: Simple Comparative Experiments
  • 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
  • 2.7 Problems
• CHAPTER 3: Experiments with a Single Factor: The Analysis of Variance
  • 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
  • 3.12 Problems
• CHAPTER 4: Randomized Blocks, Latin Squares, and Related Designs
  • 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
  • 4.5 Problems
• CHAPTER 5: Introduction to Factorial Designs
  • 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
  • 5.7 Problems
• CHAPTER 6: The 2k Factorial Design
  • 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
  • 6.10 Problems
• CHAPTER 7: Blocking and Confounding in the 2k Factorial Design
  • 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
  • 7.9 Problems
• CHAPTER 8: Two‐Level Fractional Factorial Designs
  • 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
  • 8.10 Problems
• CHAPTER 9: Additional Design and Analysis Topics for Factorial and Fractional Factorial Designs
  • 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
  • 9.7 Problems
• CHAPTER 10: Fitting Regression Models
  • 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
  • 10.9 Problems
• CHAPTER 11: Response Surface Methods and Designs
  • 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
  • 11.8 Problems
• CHAPTER 12: Robust Parameter Design and Process Robustness Studies
  • 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
  • 12.6 Problems
• CHAPTER 13: Experiments with Random Factors
  • 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
  • 13.7 Problems
• CHAPTER 14: Nested and Split‐Plot Designs
  • 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
  • 14.6 Problems
• CHAPTER 15: Other Design and Analysis Topics
  • 15.1 Nonnormal Responses and Transformations
  • 15.2 Unbalanced Data in a Factorial Design
  • 15.3 The Analysis of Covariance
  • 15.4 Repeated Measures
  • 15.5 Problems
• Appendix
• Bibliography
• Index
• End User License Agreement

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