Design and Analysis of Experiments

ISBN-10: 0470128666

ISBN-13: 9780470128664

Edition: 7th 2009

Authors: Douglas C. Montgomery, Douglas C. Montgomery

List price: $212.95
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This bestselling professional reference has helped over 100,000 engineers and scientists with the success of their experiments. The new edition includes more software examples taken from the three most dominant programs in the field: Minitab, JMP, and SAS. Additional material has also been added in several chapters, including new developments in robust design and factorial designs. New examples and exercises are also presented to illustrate the use of designed experiments in service and transactional organizations. Engineers will be able to apply this information to improve the quality and efficiency of working systems.
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Book details

List price: $212.95
Edition: 7th
Copyright year: 2009
Publisher: John Wiley & Sons, Incorporated
Publication date: 7/28/2008
Binding: Hardcover
Pages: 680
Size: 8.00" wide x 10.00" long x 1.00" tall
Weight: 2.970
Language: English

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
Simple Comparative Experiments.
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
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
A Real Economy Application of a Designed Experiment
Discovering Dispersion Effects
The Regression Approach to the Analysis of Variance
Nonparametric Methods in the Analysis of Variance
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
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
The 2<sup>k</sup> Factorial Design.
The 2<sup>2</sup> Design
The 2<sup>3</sup> Design
The General 2<sup>k</sup> Design
A Single Replicate of the 2<sup>k</sup> Design
Additional Examples of Unreplicated 2<sup>k</sup> Design
2<sup>k</sup> Designs are Optimal Designs
The Addition of Center Points to the 2<sup>k</sup> Design
Why We Work with Coded Design Variables
Blocking and Confounding in the 2<sup>k</sup> Factorial Design.
Blocking a Replicated 2<sup>k</sup> Factorial Design
Confounding in the 2<sup>k</sup> Factorial Design
Confounding the 2<sup>k</sup> Factorial Design in Two Blocks
Another Illustration of Why Blocking Is Important
Confounding the 2<sup>k</sup> Factorial Design in Four Blocks
Confounding the 2<sup>k</sup> Factorial Design in 2<sup>p</sup> Blocks
Partial Confounding
Two-Level Fractional Factorial Designs.
The One-Half Fraction of the 2<sup>k</sup> Design
The One-Quarter Fraction of the 2<sup>k</sup> Design
The General 2<sup>k�p</sup> Fractional Factorial Design
Alias Structures in Fractional Factorials and other Designs
Resolution III Designs
Resolution IV and V Designs
Supersaturated Designs
Three-Level and Mixed-Level Factorial and Fractional Factorial Designs.
The 3<sup>k</sup> Factorial Design
Confounding in the 3<sup>k</sup> Factorial Design
Fractional Replication of the 3<sup>k</sup> Factorial Design
Factorials with Mixed Levels
Fitting Regression Models.
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
Response Surface Methods and Designs.
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
Robust Parameter Design and Process Robustness Studies.
Crossed Array Designs
Analysis of the Crossed Array Design
Combined Array Design and the Response Model Approach
Choice of Designs
Experiments with Random Factors.
The Random Effects Model
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
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
Other Design and Analysis Topics.
Nonnormal Responses and Transformations
Unbalanced Data in a Factorial Design
The Analysis of Covariance
Repeated Measures
Cumulative Standard Normal Distribution
Percentage Points of the t Distribution
Percentage Points of the X<sup>2</sup> 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 2<sup>k�p</sup> Fractional Factorial Designs with k <u><</u></u>15 and n <u><</u></u>64
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