Student Solutions Manual Design and Analysis of Experiments, 8e Student Solutions Manual / Edition 8 available in Paperback
Solutions Manual for Design and Analysis of Experiments, 8th Edition.The eighth edition of this best selling text 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.The eighth edition of Design and Analysis of Experiments 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.Continuing to place a strong focus on the use of the computer, this edition includes software examples taken from the four most dominant programs in the field: Design-Expert, Minitab, JMP, and SAS.
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About the Author
DOUGLAS C. MONTGOMERY, PhD, is Regents Professor of Industrial Engineering and Statistics at Arizona State University. Dr. Montgomery is a Fellow of the American Statistical Association, the American Society for Quality, the Royal Statistical Society, and the Institute of Industrial Engineers and has more than thirty years of academic and consulting experience. He has devoted his research to engineering statistics, specifically the design and analysis of experiments, statistical methods for process monitoring and optimization, and the analysis of time-oriented data. Dr. Montgomery is the coauthor of Generalized Linear Models: With Applications in Engineering and the Sciences, Second Edition and Introduction to Time Series Analysis and Forecasting, both published by Wiley.
Table of Contents
Simple Comparative Experiments.
Experiments with a Single Factor: The Analysis of Variance.
Randomized Blocks, Latin Squares, and Related Designs.
Introduction to Factorial Designs.
The 2k Factorial Design.
Blocking and Confounding in the 2k Factorial Design.
Two-Level Fractional Factorial Designs.
Three-Level and Mixed-Level Factorial and Fractional Factorial Designs.
Fitting Regression Models.
Response Surface Methods and Other Approaches to Process Optimization.
Experiments with Random Factors.
Nested and Split-Plot Designs.
Other Design and Analysis Topics.