Design and Analysis of Gauge R and R Studies: Making Decisions with Confidence Intervals in Random and Mixed ANOVA Models
Autor Richard K. Burdick, Connie M. Borror, Douglas C. Montgomeryen Limba Engleză Paperback – 31 dec 1986
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Specificații
ISBN-13: 9780898715880
ISBN-10: 0898715881
Pagini: 220
Ilustrații: Illustrations
Dimensiuni: 177 x 253 x 11 mm
Greutate: 0 kg
Editura: Society for Industrial and Applied Mathematics
Colecția Society for Industrial and Applied Mathematics
Locul publicării:Philadelphia, United States
ISBN-10: 0898715881
Pagini: 220
Ilustrații: Illustrations
Dimensiuni: 177 x 253 x 11 mm
Greutate: 0 kg
Editura: Society for Industrial and Applied Mathematics
Colecția Society for Industrial and Applied Mathematics
Locul publicării:Philadelphia, United States
Cuprins
Preface; 1. Introduction; 2. Balanced One-Factor Random Models; 3. Balanced Two-Factor Crossed Random Models with Interaction; 4. Design of Gauge R&R Experiments; 5. Balanced Two-Factor Crossed Random Models with No Interaction; 6. Balanced Two-Factor Crossed Mixed Models; 7. Unbalanced One- and Two-Factor Models; 8. Strategies for Constructing Intervals with ANOVA Models; Appendix A. The Analysis of Variance; Appendix B. MLS and GCI Methods; Appendix C. Tables of F-values; Bibliography; Index.
Recenzii
'The authors have done an excellent job of providing practitioners with an up-to-date reference for constructing confidence intervals for a class of mixed models with application to gauge R&R studies.' José G. Ramírez, W.L. Gore & Associates, Inc.
'A pattern of presentation is established in early chapters and consistently used throughout the book. The notation is also unified throughout the book, which is a major contribution.' Greg Larsen, Agilent Technologies
'A pattern of presentation is established in early chapters and consistently used throughout the book. The notation is also unified throughout the book, which is a major contribution.' Greg Larsen, Agilent Technologies
Descriere
This book provides a protocol for conducting gauge repeatability and reproducibility (R&R) experiments.