Experiments Planning, Analysis, and Optimization

by Wu, C. F. Jeff; Hamada, Michael S.

• ISBN13: 9780471699460
• ISBN10: 0471699462
• Edition: 2nd
• Format: Hardcover
• Copyright: 2009-08-10
• Publisher: Wiley

Summary

Wiley Series in Probabilty and StatisticsSecond EditionExperimentsPlanning, Analysis, and OptimizationC. F. Jeff Wu and Michael S. HamadaPraise for the First Edition:"If you . . . want an up-to-date, definitive reference written by authors who have contributed much to this field, then this book is an essential addition to your library." -Journal of the American Statistical AssociationFully updated to reflect the major progress in the use of statistically designed experiments for product and process improvement, Experiments, Second Edition introduces some of the newest discoveries-and sheds further light on existing ones-on the design and analysis of experiments and their applications in system optimization, robustness, and treatment comparison. Maintaining the same easy-to-follow style as the previous edition while also including modern updates, this book continues to present a new and integrated system of experimental design and analysis that can be applied across various fields of research including engineering, medicine, and the physical sciences.The authors modernize accepted methodologies while refining many cutting-edge topics including robust parameter design, reliability improvement, analysis of non-normal data, analysis of experiments with complex aliasing, multilevel designs, minimum aberration designs, and orthogonal arrays. Along with a new chapter that focuses on regression analysis, the Second Edition features expanded and new coverage of additional topics, including:Expected mean squares and sample size determinationOne-way and two-way ANOVA with random effectsSplit-plot designsANOVA treatment of factorial effectsResponse surface modeling for related factorsDrawing on examples from their combined years of working with industrial clients, the authors present many cutting-edge topics in a single, easily accessible source. Extensive case studies, including goals, data, and experimental designs, are also included, and the book's data sets can be found on a related FTP site, along with additional supplemental material. Chapter summaries provide a succinct outline of discussed methods, and extensive appendices direct readers to resources for further study.Experiments, Second Edition is an excellent book for design of experiments courses at the upper-undergraduate and graduate levels. It is also a valuable resource for practicing engineers and statisticians.

Author Biography

C. F. Jeff Wu, PhD, is Coca-Cola Professor in Engineering Statistics at the Georgia Institute of Technology. Dr. Wu has published more than 130 papers and is the recipient of numerous accolades, including the including the National Academy of Engineering membership and the COPSS Presidents' Award.

Michael S. Hamada, PhD, is Statistical Scientist at Los Alamos National Laboratory in New Mexico. Dr. Hamada is a Fellow of the American Statistical Association and the author of more than seventy published papers.

Table of Contents

Basic Concepts for Experimental Design and Introductory Regression Analysis

Introduction and Historical Perspective

A Systematic Approach to the Planning and Implementation of Experiments

Fundamental Principles: Replication, Randomization, and Blocking

Simple Linear Regression

Testing of Hypothesis and Interval Estimation

Multiple Linear Regression

Variable Selection in Regression Analysis

Analysis of Air Pollution Data

Practical Summary

Experiments with a Single Factor

One-Way Layout

Multiple Comparisons

Quantitative Factors and Orthogonal Polynomials

Expected Mean Squares and Sample Size Determination

One-Way Random Effects Model

Residual Analysis: Assessment of Model Assumptions

Practical Summary

Experiments with More Than One Factor

Paired Comparison Designs

Randomized Block Designs

Two-Way Layout: Factors With Fixed Levels

Two-Way Layout: Factors With Random Levels

Multi-Way Layout

Latin Square Designs: Two Blocking Variables

Graeco-Latin Square Designs

Balanced Incomplete Block Designs

Split-Plot Designs

Analysis of Covariance: Incorporating Auxiliary Information

Transformation of the Response

Practical Summary

Full Factorial Experiments at Two Levels

An Epitaxial Layer Growth Experiment

Full Factorial Designs at Two Levels: A General Discussion

Factorial Effects and Plots

Using Regression to Compute Factorial Effects

ANOVA Treatment of Factorial Effects

Fundamental Principles for Factorial Effects: Effect Hierarchy, Effect Sparsity, and Effect Heredity

Comparisons with the One-Factor-At-A-Time" Approach

Normal and Half-Normal Plots for Judging Effect Significance

Lenth's Method: Testing Effect Significance for Experiments Without Variance Estimates

Nominal-the-Best Problem and Quadratic Loss Function

Use of Log Sample Variance for Dispersion Analysis

Analysis of Location and Dispersion: Revisiting the Epitaxial Layer Growth Experiment

Test of Variance Homogeneity and Pooled Estimate of Variance

Studentized Maximum Modulus Test: Testing Effect Significance for Experiments With Variance Estimates

Blocking and Optimal Arrangement of 2k Factorial Designs in 2q Blocks

Practical Summary

Fractional Factorial Experiments at Two Levels

A Leaf Spring Experiment

Fractional Factorial Designs: Effect Aliasing and the Criteria Of Resolution and Minimum Aberration

Analysis of Fractional Factorial Experiments

Techniques for Resolving the Ambiguities in Aliased Effects

Selection of 2kp Designs Using Minimum Aberration and Related Criteria

Blocking in Fractional Factorial Designs

Practical Summary

Full Factorial and Fractional Factorial Experiments at Three.Levels

A Seat-Belt Experiment

Larger-the-Better and Smaller-the-Better Problems

3k Full Factorial Designs

3kp Fractional Factorial Designs

Simple Analysis Methods: Plots and Analysis of Variance

An Alternative Analysis Method

Analysis Strategies for Multiple Responses I: Out-Of-Spec Probabilities

Blocking in 3k and 3kp Designs

Practical Summary

Other Design and Analysis Techniques for Experiments at More Than Two Levels

A Router Bit Experiment Based on a Mixed Two-Level and Four-Level Design

Method of Replacement and Construction of 2m4n Designs

Minimum Aberration 2m4n Designs

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