Design and Analysis of Experiments

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

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

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

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

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

Chapter 6: The 2_k_ Factorial Design

• • 6.1 Introduction
• • 6.2 The 22 Design
• • 6.3 The 23 Design
• • 6.4 The General 2_k_ Design
• • 6.5 A Single Replicate of the 2_k_ Design
• • 6.6 Additional Examples of Unreplicated 2_k_ Designs
• • 6.7 2_k_ Designs are Optimal Designs
• • 6.8 The Addition of Center Points to the 2_k_ Design
• • 6.9 Why We Work with Coded Design Variables

Chapter 7: Blocking and Confounding in the 2_k_ Factorial Design

• • 7.1 Introduction
• • 7.2 Blocking a Replicated 2_k_ Factorial Design
• • 7.3 Confounding in the 2_k_ Factorial Design
• • 7.4 Confounding the 2_k_ Factorial Design in Two Blocks
• • 7.5 Another Illustration of Why Blocking is Important
• • 7.6 Confounding the 2_k_ Factorial Design in Four Blocks
• • 7.7 Confounding the 2_k_ Factorial Design in 2_p_ Blocks
• • 7.8 Partial Confounding

Chapter 8: Two-Level Fractional Factorial Designs

• • 8.1 Introduction
• • 8.2 The One-Half Fraction of the 2_k_ Design
• • 8.3 The One-Quarter Fraction of the 2_k_ Design
• • 8.4 The General 2_k_−_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

• • 9.1 The 3_k_ Factorial Design
• • 9.2 Confounding in the 3_k_ Factorial Design
• • 9.3 Fractional Replication of the 3_k_ 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

• • 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

• • 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

• • 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

• • 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

• • 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 (Available in e-text for students)