Statistical Design and Analysis of Experiments: With Applications to Engineering and Science / Edition 1

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Overview

Ideal for both students and professionals, this focused and cogent reference has proven to be an excellent classroom textbook with numerous examples. It deserves a place among the tools of every engineer and scientist working in an experimental setting.
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Editorial Reviews

Booknews
Featuring numerous examples, the authors treat statistics as an integral component of experimentation from the planning stage to presentation of the conclusions. The book provides background information, presents elementary descriptive statistics and graphical displays, and discusses experimental design and analysis. The final part is devoted to regression modelling. Annotation c. Book News, Inc., Portland, OR (booknews.com)
From the Publisher
"With an excellent presentation, this is suitable as a textbook in a graduate level course in design of experiments." (Journal of Statistical Computation and Simulation, April 2005)

"...can really provide useful information for the intended audience..." (Zentralblatt Math, Vol. 1029, 2004)

“...a practitioner’s guide to statistical methods for designing and analyzing experiments...” (Quarterly of Applied Mathematics, Vol. LXI, No. 3, September 2003)

"...a perfect desktop reference..." (Technometrics, Vol. 45, No. 3, August 2003)

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Product Details

  • ISBN-13: 9780471853640
  • Publisher: Wiley, John & Sons, Incorporated
  • Publication date: 1/28/1989
  • Series: Wiley Series in Probability and Statistics Series , #221
  • Edition description: Older Edition
  • Edition number: 1
  • Pages: 720
  • Product dimensions: 6.35 (w) x 9.51 (h) x 1.49 (d)

Meet the Author

ROBERT L. MASON, PhD, is Institute Analyst at Southwest Research Institute in San Antonio, Texas.

RICHARD F. GUNST, PhD, is a professor in the Department of Statistical Science at Southern Methodist University in Dallas, Texas.

JAMES L. HESS, PhD, is Staff Vice President, Operations, at Leggett & Platt Inc. in Carthage, Missouri.

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Table of Contents

Preface
Pt. I Fundamental Statistical Concepts 1
1 Statistics in Engineering and Science 3
2 Fundamentals of Statistical Inference 33
3 Inference on Means and Standard Deviation 69
Pt. II Design and Analysis with Factorial Structure 107
4 Statistical Principles in Experimental Design 109
5 Factorial Experiments in Completely Randomized Designs 140
6 Analysis of Completely Randomized Designs 170
7 Fractional Factorial Experiments 228
8 Analysis of Fractional Factorial Experiments 271
Pt. III Design and Analysis with Random Effects 309
9 Experiments in Randomized Block Designs 311
10 Analysis of Designs with Random Factor Levels 347
11 Nested Designs 378
12 Special Designs for Process Improvement 400
13 Analysis of Nested Designs and Designs for Process Improvement 423
Pt. IV Design and Analysis with Quantitative Predictors and Factors 459
14 Linear Regression with One Predictor Variable 461
15 Linear Regression with Several Predictor Variables 496
16 Linear Regression with Factors and Covariates as Predictors 535
17 Designs and Analyses for Fitting Response Surfaces 568
18 Model Assessment 614
19 Variable Selection Techniques 659
App.: Statistical Tables 689
Index 723
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