Design and Analysis of Experiments, 9th Edition

Design and Analysis of Experiments, 9th Edition

by Douglas C. Montgomery
Released May 2017
Publisher(s): Wiley
ISBN: 9781119320937

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Book description

Design and Analysis of Experiments, 9th Edition continues to help senior and graduate students in engineering, business, and statistics--as well as working practitioners--to design and analyze experiments for improving the quality, efficiency and performance of working systems. This bestselling text maintains its comprehensive coverage by including: new examples, exercises, and problems (including in the areas of biochemistry and biotechnology); new topics and problems in the area of response surface; new topics in nested and split-plot design; and the residual maximum likelihood method is now emphasized throughout the book.

Table of contents

  1. Cover
  2. Title Page
  3. Preface
    1. Audience
    2. About the Book
    3. Course Suggestions
    4. The Supplemental Text Material
    5. Website
    6. Acknowledgments
  4. CHAPTER 1: Introduction
    1. 1.1 Strategy of Experimentation
    2. 1.2 Some Typical Applications of Experimental Design
    3. 1.3 Basic Principles
    4. 1.4 Guidelines for Designing Experiments
    5. 1.5 A Brief History of Statistical Design
    6. 1.6 Summary: Using Statistical Techniques in Experimentation
    7. 1.7 Problems
  5. CHAPTER 2: Simple Comparative Experiments
    1. 2.1 Introduction
    2. 2.2 Basic Statistical Concepts
    3. 2.3 Sampling and Sampling Distributions
    4. 2.4 Inferences About the Differences in Means, Randomized Designs
    5. 2.5 Inferences About the Differences in Means, Paired Comparison Designs
    6. 2.6 Inferences About the Variances of Normal Distributions
    7. 2.7 Problems
  6. CHAPTER 3: Experiments with a Single Factor: The Analysis of Variance
    1. 3.1 An Example
    2. 3.2 The Analysis of Variance
    3. 3.3 Analysis of the Fixed Effects Model
    4. 3.4 Model Adequacy Checking
    5. 3.5 Practical Interpretation of Results
    6. 3.6 Sample Computer Output
    7. 3.7 Determining Sample Size
    8. 3.8 Other Examples of Single-Factor Experiments
    9. 3.9 The Random Effects Model
    10. 3.10 The Regression Approach to the Analysis of Variance
    11. 3.11 Nonparametric Methods in the Analysis of Variance
    12. 3.12 Problems
  7. CHAPTER 4: Randomized Blocks, Latin Squares, and Related Designs
    1. 4.1 The Randomized Complete Block Design
    2. 4.2 The Latin Square Design
    3. 4.3 The Graeco-Latin Square Design
    4. 4.4 Balanced Incomplete Block Designs
    5. 4.5 Problems
  8. CHAPTER 5: Introduction to Factorial Designs
    1. 5.1 Basic Definitions and Principles
    2. 5.2 The Advantage of Factorials
    3. 5.3 The Two-Factor Factorial Design
    4. 5.4 The General Factorial Design
    5. 5.5 Fitting Response Curves and Surfaces
    6. 5.6 Blocking in a Factorial Design
    7. 5.7 Problems
  9. CHAPTER 6: The 2k Factorial Design
    1. 6.1 Introduction
    2. 6.2 The 22 Design
    3. 6.3 The 23 Design
    4. 6.4 The General 2k Design
    5. 6.5 A Single Replicate of the 2k Design
    6. 6.6 Additional Examples of Unreplicated 2k Designs
    7. 6.7 2k Designs are Optimal Designs
    8. 6.8 The Addition of Center Points to the 2k Design
    9. 6.9 Why We Work with Coded Design Variables
    10. 6.10 Problems
  10. CHAPTER 7: Blocking and Confounding in the 2k Factorial Design
    1. 7.1 Introduction
    2. 7.2 Blocking a Replicated 2k Factorial Design
    3. 7.3 Confounding in the 2k Factorial Design
    4. 7.4 Confounding the 2k Factorial Design in Two Blocks
    5. 7.5 Another Illustration of Why Blocking Is Important
    6. 7.6 Confounding the 2k Factorial Design in Four Blocks
    7. 7.7 Confounding the 2k Factorial Design in 2p Blocks
    8. 7.8 Partial Confounding
    9. 7.9 Problems
  11. CHAPTER 8: Two‐Level Fractional Factorial Designs
    1. 8.1 Introduction
    2. 8.2 The One‐Half Fraction of the 2k Design
    3. 8.3 The One‐Quarter Fraction of the 2k Design
    4. 8.4 The General 2k–p Fractional Factorial Design
    5. 8.5 Alias Structures in Fractional Factorials and Other Designs
    6. 8.6 Resolution III Designs
    7. 8.7 Resolution IV and V Designs
    8. 8.8 Supersaturated Designs
    9. 8.9 Summary
    10. 8.10 Problems
  12. CHAPTER 9: Additional Design and Analysis Topics for Factorial and Fractional Factorial Designs
    1. 9.1 The 3k Factorial Design
    2. 9.2 Confounding in the 3k Factorial Design
    3. 9.3 Fractional Replication of the 3k Factorial Design
    4. 9.4 Factorials with Mixed Levels
    5. 9.5 Nonregular Fractional Factorial Designs
    6. 9.6 Constructing Factorial and Fractional Factorial Designs Using an Optimal Design Tool
    7. 9.7 Problems
  13. CHAPTER 10: Fitting Regression Models
    1. 10.1 Introduction
    2. 10.2 Linear Regression Models
    3. 10.3 Estimation of the Parameters in Linear Regression Models
    4. 10.4 Hypothesis Testing in Multiple Regression
    5. 10.5 Confidence Intervals in Multiple Regression
    6. 10.6 Prediction of New Response Observations
    7. 10.7 Regression Model Diagnostics
    8. 10.8 Testing for Lack of Fit
    9. 10.9 Problems
  14. CHAPTER 11: Response Surface Methods and Designs
    1. 11.1 Introduction to Response Surface Methodology
    2. 11.2 The Method of Steepest Ascent
    3. 11.3 Analysis of a Second‐Order Response Surface
    4. 11.4 Experimental Designs for Fitting Response Surfaces
    5. 11.5 Experiments with Computer Models
    6. 11.6 Mixture Experiments
    7. 11.7 Evolutionary Operation
    8. 11.8 Problems
  15. CHAPTER 12: Robust Parameter Design and Process Robustness Studies
    1. 12.1 Introduction
    2. 12.2 Crossed Array Designs
    3. 12.3 Analysis of the Crossed Array Design
    4. 12.4 Combined Array Designs and the Response Model Approach
    5. 12.5 Choice of Designs
    6. 12.6 Problems
  16. CHAPTER 13: Experiments with Random Factors
    1. 13.1 Random Effects Models
    2. 13.2 The Two‐Factor Factorial with Random Factors
    3. 13.3 The Two‐Factor Mixed Model
    4. 13.4 Rules for Expected Mean Squares
    5. 13.5 Approximate F‐Tests
    6. 13.6 Some Additional Topics on Estimation of Variance Components
    7. 13.7 Problems
  17. CHAPTER 14: Nested and Split‐Plot Designs
    1. 14.1 The Two‐Stage Nested Design
    2. 14.2 The General m‐Stage Nested Design
    3. 14.3 Designs with Both Nested and Factorial Factors
    4. 14.4 The Split‐Plot Design
    5. 14.5 Other Variations of the Split‐Plot Design
    6. 14.6 Problems
  18. CHAPTER 15: Other Design and Analysis Topics
    1. 15.1 Nonnormal Responses and Transformations
    2. 15.2 Unbalanced Data in a Factorial Design
    3. 15.3 The Analysis of Covariance
    4. 15.4 Repeated Measures
    5. 15.5 Problems
  19. Appendix
  20. Bibliography
  21. Index
  22. End User License Agreement

Product information

  • Title: Design and Analysis of Experiments, 9th Edition
  • Author(s): Douglas C. Montgomery
  • Release date: May 2017
  • Publisher(s): Wiley
  • ISBN: 9781119320937