Description

Book Synopsis
Emphasizes the strategy of experimentation, data analysis, and the interpretation of experimental results. * Features numerous examples using actual engineering and scientific studies. * Presents statistics as an integral component of experimentation from the planning stage to the presentation of the conclusions.

Trade Review
"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)



Table of Contents
Preface.

PART I: FUNDAMENTAL STATISTICAL CONCEPTS.

Statistics in Engineering and Science.

Fundamentals of Statistical Inference.

Inferences on Means and Standard Deviations.

PART II: DESIGN AND ANALYSIS WITH FACTORIAL STRUCTURE.

Statistical Principles in Experimental Design.

Factorial Experiments in Completely Randomized Designs.

Analysis of Completely Randomized Designs.

Fractional Factorial Experiments.

Analysis of Fractional Factorial Experiments.

PART III: DESIGN AND ANALYSIS WITH RANDOM EFFECTS.

Experiments in Randomized Block Designs.

Analysis of Designs with Random Factor Levels.

Nested Designs.

Special Designs for Process Improvement.

Analysis of Nested Designs and Designs for Process Improvement.

PART IV: DESIGN AND ANALYSIS WITH QUANTITATIVE PREDICTORS AND FACTORS.

Linear Regression with One Predicator Variables.

Linear Regression with Several Predicator Variables.

Linear Regression with Factors and Covariates as Predictors.

Designs and Analyses for Fitting Re sponse Surfaces.

Model Assessment.

Variable Selection Techniques.

Appendix: Statistical Tables.

Index.

Statistical Design and Analysis of Experiments

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    A Hardback by Robert L. Mason, Richard F. Gunst, James L. Hess

      Trusted by thousands of customers. See 2,385+ Customer Reviews

      View other formats and editions of Statistical Design and Analysis of Experiments by Robert L. Mason

      Publisher: John Wiley & Sons Inc
      Publication Date: 25/02/2003
      ISBN13: 9780471372165, 978-0471372165
      ISBN10: 0471372161

      Description

      Book Synopsis
      Emphasizes the strategy of experimentation, data analysis, and the interpretation of experimental results. * Features numerous examples using actual engineering and scientific studies. * Presents statistics as an integral component of experimentation from the planning stage to the presentation of the conclusions.

      Trade Review
      "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)



      Table of Contents
      Preface.

      PART I: FUNDAMENTAL STATISTICAL CONCEPTS.

      Statistics in Engineering and Science.

      Fundamentals of Statistical Inference.

      Inferences on Means and Standard Deviations.

      PART II: DESIGN AND ANALYSIS WITH FACTORIAL STRUCTURE.

      Statistical Principles in Experimental Design.

      Factorial Experiments in Completely Randomized Designs.

      Analysis of Completely Randomized Designs.

      Fractional Factorial Experiments.

      Analysis of Fractional Factorial Experiments.

      PART III: DESIGN AND ANALYSIS WITH RANDOM EFFECTS.

      Experiments in Randomized Block Designs.

      Analysis of Designs with Random Factor Levels.

      Nested Designs.

      Special Designs for Process Improvement.

      Analysis of Nested Designs and Designs for Process Improvement.

      PART IV: DESIGN AND ANALYSIS WITH QUANTITATIVE PREDICTORS AND FACTORS.

      Linear Regression with One Predicator Variables.

      Linear Regression with Several Predicator Variables.

      Linear Regression with Factors and Covariates as Predictors.

      Designs and Analyses for Fitting Re sponse Surfaces.

      Model Assessment.

      Variable Selection Techniques.

      Appendix: Statistical Tables.

      Index.

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