| Titre : | Experiments : planning, analysis, and parameter design optimization | | Type de document : | texte imprimé | | Auteurs : | Jian Fu Shao, Auteur ; Hamada, Michael S., Auteur | | Mention d'édition : | 2e éd. | | Editeur : | New York : Wiley | | Année de publication : | 2000 | | Collection : | Wiley series in probability and statistics | | Importance : | 716 p. | | Présentation : | ill. | | Format : | 24 cm | | ISBN/ISSN/EAN : | 978-0-471-69946-0 | | Langues : | Français (fre) | | Mots-clés : | planning -- analysis -- parameter design optimization | | Index. décimale : | 519.863 Modèles d'optimisation | | Résumé : | Fully updated to reflect the major progress in the use of statistically designed experiments for product and process improvement, Experiments, Second Edition introduces some of the newest discoveries—and sheds further light on existing ones—on the design and analysis of experiments and their applications in system optimization, robustness, and treatment comparison. Maintaining the same easy-to-follow style as the previous edition while also including modern updates, this book continues to present a new and integrated system of experimental design and analysis that can be applied across various fields of research including engineering, medicine, and the physical sciences.
The authors modernize accepted methodologies while refining many cutting-edge topics including robust parameter design, reliability improvement, analysis of non-normal data, analysis of experiments with complex aliasing, multilevel designs, minimum aberration designs, and orthogonal arrays. Along with a new chapter that focuses on regression analysis, the Second Edition features expanded and new coverage of additional topics, including:
Expected mean squares and sample size determination
One-way and two-way ANOVA with random effects
Split-plot designs
ANOVA treatment of factorial effects
Response surface modeling for related factors
Drawing on examples from their combined years of working with industrial clients, the authors present many cutting-edge topics in a single, easily accessible source. Extensive case studies, including goals, data, and experimental designs, are also included, and the book's data sets can be found on a related FTP site, along with additional supplemental material. Chapter summaries provide a succinct outline of discussed methods, and extensive appendices direct readers to resources for further study.
Experiments, Second Edition is an excellent book for design of experiments courses at the upper-undergraduate and graduate levels. It is also a valuable resource for practicing engineers and statisticians. | | Note de contenu : | 1 Basic Concepts for Experimental Design and Introductory Regression Analysis.
2 Experiments with a Single Factor.
3 Experiments with More Than One Factor.
4 Full Factorial Experiments at Two Levels.
5 Fractional Factorial Experiments at Two Levels.
6 Full Factorial and Fractional Factorial Experiments at Three Levels.
7 Other Design and Analysis Techniques for Experiments at More Than Two Levels.
8 Nonregular Designs: Construction and Properties.
9 Experiments with Complex Aliasing.
10 Response Surface Methodology.
11 Introduction to Robust Parameter Design.
12 Robust Parameter Design for Signal-Response Systems.13 Experiments for Improving Reliability.
14 Analysis of Experiments with Nonnormal Data. | | En ligne : | http://books.google.dz/books?id=63n8QAAACAAJ&hl=fr&source=gbs_ViewAPI&redir_esc= [...] |
Experiments : planning, analysis, and parameter design optimization [texte imprimé] / Jian Fu Shao, Auteur ; Hamada, Michael S., Auteur . - 2e éd. . - Wiley, 2000 . - 716 p. : ill. ; 24 cm. - ( Wiley series in probability and statistics) . ISBN : 978-0-471-69946-0 Langues : Français ( fre) | Mots-clés : | planning -- analysis -- parameter design optimization | | Index. décimale : | 519.863 Modèles d'optimisation | | Résumé : | Fully updated to reflect the major progress in the use of statistically designed experiments for product and process improvement, Experiments, Second Edition introduces some of the newest discoveries—and sheds further light on existing ones—on the design and analysis of experiments and their applications in system optimization, robustness, and treatment comparison. Maintaining the same easy-to-follow style as the previous edition while also including modern updates, this book continues to present a new and integrated system of experimental design and analysis that can be applied across various fields of research including engineering, medicine, and the physical sciences.
The authors modernize accepted methodologies while refining many cutting-edge topics including robust parameter design, reliability improvement, analysis of non-normal data, analysis of experiments with complex aliasing, multilevel designs, minimum aberration designs, and orthogonal arrays. Along with a new chapter that focuses on regression analysis, the Second Edition features expanded and new coverage of additional topics, including:
Expected mean squares and sample size determination
One-way and two-way ANOVA with random effects
Split-plot designs
ANOVA treatment of factorial effects
Response surface modeling for related factors
Drawing on examples from their combined years of working with industrial clients, the authors present many cutting-edge topics in a single, easily accessible source. Extensive case studies, including goals, data, and experimental designs, are also included, and the book's data sets can be found on a related FTP site, along with additional supplemental material. Chapter summaries provide a succinct outline of discussed methods, and extensive appendices direct readers to resources for further study.
Experiments, Second Edition is an excellent book for design of experiments courses at the upper-undergraduate and graduate levels. It is also a valuable resource for practicing engineers and statisticians. | | Note de contenu : | 1 Basic Concepts for Experimental Design and Introductory Regression Analysis.
2 Experiments with a Single Factor.
3 Experiments with More Than One Factor.
4 Full Factorial Experiments at Two Levels.
5 Fractional Factorial Experiments at Two Levels.
6 Full Factorial and Fractional Factorial Experiments at Three Levels.
7 Other Design and Analysis Techniques for Experiments at More Than Two Levels.
8 Nonregular Designs: Construction and Properties.
9 Experiments with Complex Aliasing.
10 Response Surface Methodology.
11 Introduction to Robust Parameter Design.
12 Robust Parameter Design for Signal-Response Systems.13 Experiments for Improving Reliability.
14 Analysis of Experiments with Nonnormal Data. | | En ligne : | http://books.google.dz/books?id=63n8QAAACAAJ&hl=fr&source=gbs_ViewAPI&redir_esc= [...] |
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