Design and Analysis of Experiments, Student Solutions Manual, 5th Edition

by Douglas C. Montgomery (Arizona State Univ.)

• ISBN13: 9780471265917
• ISBN10: 0471265918
• Edition: 5th
• Format: Paperback
• Copyright: 2002-08-01
• Publisher: Wiley

Summary

Learn How to Achieve Optimal Industrial Experimentation Through four editions, Douglas Montgomery has provided statisticians, engineers, scientists, and managers with the most effective approach for learning how to design, conduct, and analyze experiments that optimize performance in products and processes. Now, in this fully revised and enhanced Fifth Edition, Montgomery has improved his best-selling text by focusing even more sharply on factorial and fractional factorial design and presenting new analysis techniques (including the generalized linear model). There is also expanded coverage of experiments with random factors, response surface methods, experiments with mixtures, and methods for process robustness studies. The book also illustrates two of today's most powerful software tools for experimental design: Design-Expert(r) and Minitab(r). Throughout the text, You'll find output from these two programs, along with detailed discussion on how computers are currently used in the analysis and design of experiments. You'll also learn how to use statistically designed experiments to:* Obtain information for characterization and optimization of systems* Improve manufacturing processes* Design and develop new processes and products* Evaluate material alternatives in product design* Improve the field performance, reliability, and manufacturing aspects of products* Learn how to conduct experiments effectively and efficientlyOther important textbook features:* Student version of Design-Expert(r) software is available.* Web site (www.wiley.com/college/montgomery) offers supplemental text material for each chapter, a sample syllabus, and sample student projects from the author's Design of Experiments course at Arizona State University.

Table of Contents

Simple Comparative Experiments

Experiments with a Single Factor: The Analysis of Variance

More About Single-Factor Experiments

Randomized Blocks, Latin Squares, and Related Designs

Introduction to Factorial Designs

The 2 k Factorial Design

Blocking and Confounding in the 2 k Factorial Design

Two-Level Fractional Factorial Designs

Three-Level and Mixed-Level Factorial and Fractional Factorial Designs

Factorial Experiments with Random Factors

Nested and Split-Plot Designs

Fitting Regression Models

Response Surface Methods and Other Approaches to Process Optimization

Bibliography

Appendix

Tables

Index

Table of Contents provided by Publisher. All Rights Reserved.