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Design and Analysis of Experiments

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ISBN-10: 1118146921

ISBN-13: 9781118146927

Edition: 8th 2013

Authors: Douglas C. Montgomery

List price: $241.95
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Description:

The eighth edition of Design and Analysis of Experiments continues to provide extensive and in–depth information on engineering, business, and statistics–as well as informative ways to help readers design and analyze experiments for improving the quality, efficiency and performance of working systems.  Furthermore, the 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.
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Book details

List price: $241.95
Edition: 8th
Copyright year: 2013
Publisher: John Wiley & Sons, Incorporated
Publication date: 4/10/2012
Binding: Hardcover
Pages: 752
Size: 8.00" wide x 10.00" long x 0.75" tall
Weight: 3.300
Language: English

Preface
Introduction
Strategy of Experimentation
Some Typical Applications of Experimental Design
Basic Principles
Guidelines for Designing Experiments
A Brief History of Statistical Design
Summary: Using Statistical Techniques in Experimentation
Problems
Simple Comparative Experiments
Introduction
Basic Statistical Concepts
Sampling and Sampling Distributions
Inferences About the Differences in Means, Randomized Designs
Inferences About the Differences in Means, Paired Comparison Designs
Inferences About the Variances of Normal Distributions
Problems
Experiments with a Single Factor: The Analysis of Variance
An Example
The Analysis of Variance
Analysis of the Fixed Effects Model
Model Adequacy Checking
Practical Interpretation of Results
Sample Computer Output
Determining Sample Size
Other Examples of Single-Factor Experiments
The Random Effects Model
The Regression Approach to the Analysis of Variance
Nonparametric Methods in the Analysis of Variance
Problems
Randomized Blocks, Latin Squares, and Related Designs
The Randomized Complete Block Design
The Latin Square Design
The Graeco-Latin Square Design
Balanced Incomplete Block Designs
Problems
Introduction to Factorial Designs
Basic Definitions and Principles
The Advantage of Factorials
The Two-Factor Factorial Design
The General Factorial Design
Fitting Response Curves and Surfaces
Blocking in a Factorial Design
Problems
The 2k Factorial Design
Introduction
The 22 Design
The 23 Design
The General 2k Design
A Single Replicate of the 2k Design
Additional Examples of Unreplicated 2k Design
2k Designs are Optimal Designs
The Addition of Center Points to the 2k Design
Why We Work with Coded Design Variables
Problems
Blocking and Confounding in the 2k Factorial Design
Introduction
Blocking a Replicated 2k Factorial Design
Confounding in the 2k Factorial Design
Confounding the 2k Factorial Design in Two Blocks
Another Illustration of Why Blocking Is Important
Confounding the 2k Factorial Design in Four Blocks
Confounding the 2k Factorial Design in 2p Blocks
Partial Confounding
Problems
Two-Level Fractional Factorial Designs
Introduction
The One-Half Fraction of the 2k Design
The One-Quarter Fraction of the 2k Design
The General 2k_p Fractional Factorial Design
Alias Structures in Fractional Factorials and other Designs
Resolution III Designs
Resolution IV and V Designs
Supersaturated Designs
Summary
Problems
Additional Design and Analysis Topics for Factorial and Fractional Factorial Designs
The 3k Factorial Design
Confounding in the 3k Factorial Design
Fractional Replication of the 3k Factorial Design
Factorials with Mixed Levels
Nonregular Fractional Factorial Designs
Constructing Factorial and Fractional Factorial Designs Using an Optimal Design Tool
Problems
Fitting Regression Models
Introduction
Linear Regression Models
Estimation of the Parameters in Linear Regression Models
Hypothesis Testing in Multiple Regression
Confidence Intervals in Multiple Regression
Prediction of New Response Observations
Regression Model Diagnostics
Testing for Lack of Fit
Problems
Response Surface Methods and Designs
Introduction to Response Surface Methodology
The Method of Steepest Ascent
Analysis of a Second-Order Response Surface
Experimental Designs for Fitting Response Surfaces
Experiments with Computer Models
Mixture Experiments
Evolutionary Operation
Problems
Robust Parameter Design and Process Robustness Studies
Introduction
Crossed Array Designs
Analysis of the Crossed Array Design
Combined Array Designs and the Response Model Approach
Choice of Designs
Problems
Experiments with Random Factors
Random Effects Models
The Two-Factor Factorial with Random Factors
The Two-Factor Mixed Model
Sample Size Determination with Random Effects
Rules for Expected Mean Squares
Approximate F Tests
Some Additional Topics on Estimation of Variance Components
Problems
Nested and Split-Plot Designs
The Two-Stage Nested Design
The General m-Stage Nested Design
Designs with Both Nested and Factorial Factors
The Split-Plot Design
Other Variations of the Split-Plot Design
Problems
Other Design and Analysis Topics
Nonnormal Responses and Transformations
Unbalanced Data in a Factorial Design
The Analysis of Covariance
Repeated Measures
Problems
Appendix
Cumulative Standard Normal Distribution
Percentage Points of the t Distribution
Percentage Points of the _2 Distribution
Percentage Points of the F Distribution
Operating Characteristic Curves for the Fixed Effects Model Analysis of Variance
Operating Characteristic Curves for the Random Effects Model Analysis of Variance
Percentage Points of the Studentized Range Statistic
Critical Values for Dunnett's Test for Comparing Treatments with a Control
Coefficients of Orthogonal Polynomials
Alias Relationships for 2k_p Fractional Factorial Designs with k 15 and n 64
Bibliography
Index
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