Design and Analysis of Experiments, 8/e (IE-Paperback)

Douglas C. Montgomery

  • 出版商: Wiley
  • 出版日期: 2012-05-01
  • 售價: $1,620
  • 貴賓價: 9.8$1,588
  • 語言: 英文
  • 頁數: 752
  • ISBN: 1118097939
  • ISBN-13: 9781118097939

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●The residual maximum likelihood (REML) method is now emphasized throughout the book.
●83 new homework problems (including in the areas of biochemistry and biotechnology).
●Additional examples of single-factor experiments, such as a study involving chocolate consumption and cardiovascular health (Chapter 3)
●New section on the random effects model (Chapter 3)
●New material on nonregular fractions as alternatives to traditional minimum aberration fractions in 16 runs and analysis methods for those designs discussed and illustrated (Chapter 9).
●New material on constructing factorial and fractional factorial designs using an optimal design tool (Chapter 9).
●New topics and problems in the area of response surface, including designs that combine screening and optimization and use of optimal designs (Chapter 11).
●New topics in nested and split-plot design, including the use of REML in the analysis (Chapter 14).


●Includes software examples taken from the four most dominant programs in the field: Design-Expert, Minitab, JMP, and SAS.
●Focuses on the connection between the experiment and the model that the experimenter can develop from the results of the experiement.
●Stresses the importance of experimental design as a tool for engineers and scientists to use for product design and development as well as process development and improvement. The use of experiemental design in developing products that are robust to environmental factors and other sources of variability is illustrated. The use of experimental design early in the product cycle can subsatantially reduce development lead time and cost, leading to processes and products that perform better in the field and have higher reliability than those developed using other approaches.


1 Introduction to Designed Experiments
2 Basic Statistical Methods
3 Analysis of Variance
4 Experiments with Blocking Factors
5 Factorial Experiments
6 Two-Level Factorial Designs
7 Blocking and Confounding System for Two-Level Factorials
8 Two-Level Fractional Factorial Designs
9 Other Topics on Factorial and Fractional Factorial Designs
10 Regression Modeling
11 Response Surface Methodology
12 Robust Design
13 Random Effects Models
14 Experiments with Nested Factors and Hard-to-Change Factors
15 Other Topics