First comprehensive modern treatment of ANOM will be welcomed by practitioners and statisticians as a primer and reference.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Peter R. Nelson (1949 - 2004), formerly of Clemson University, played a key role in the development of ANOM methods. In addition to authoring journal articles, books, and book chapters, he served as editor and as editorial review board member of the Journal of Quality Technology and as editorial review board member of the American Journal of Mathematical and Management Sciences. Peter was a Fellow of the ASA and ASQ.
Peter S. Wludyka is Associate Professor of Statistics at the University of North Florida, Jacksonville, and Director of the UNF Center for Research and Consulting in Statistics. He is also Biostatistical Consultant to the Office of the Dean at the University of Florida Health Sciences Center in Jacksonville, Florida. His paper on analysis of means for variances, co-authored with Peter Nelson, won the Wilcoxon Prize as best applications paper in Technometrics in 1997. Among his publications are a half dozen methodological papers on the ANOM. He has presented talks to SAS user groups on ANOM and routinely uses ANOM in collaborative research and consulting.
Karen A. F. Copeland is currently the principal statistician of Boulder Statistics, which provides statistical consulting services to clients in a variety of industry sectors, including the medical device, chemical, medical diagnostic, environmental, consumer product, food product, and tourism sectors. She held academic and industrial positions before becoming an independent consultant. Karen is a co-author of Introductory Statistics for Engineering Experimentation (Academic Press, 2003) as well as an author of peer-reviewed papers. She has developed JMP scripts for using ANOM.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Paperback. Etat : New. The analysis of means (ANOM) is a graphical procedure used to quantify differences among treatment groups in a variety of experimental design and observational study situations. The ANOM decision chart allows one to easily draw conclusions and interpret results with respect to both statistical and practical significance. It is an excellent choice for multiple comparisons of means, rates, or proportions and can be used with both balanced and unbalanced data. Key advances in ANOM procedures that have appeared only in technical journals during the last 20 years are included in this first comprehensive modern treatment of the ANOM containing all of the needed information for practitioners to understand and apply ANOM.This book contains examples from a wide variety of fields adapted from real-world applications and data with easy-to-follow, step-by-step instructions. It is front loaded, so potential ANOM users can find solutions to standard problems in the first five chapters. An appendix contains several SAS® examples showing the system's ANOM capabilities and how SAS was used to produce selected ANOM decision charts in the book.Given these features, the lack of any other book on ANOM, and the recent inclusion of ANOM in SAS, this book will be a welcome addition to practitioners' and statisticians' bookshelves, where it will serve both as a primer and reference. N° de réf. du vendeur LU-9780898715927
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Paperback. Etat : New. The analysis of means (ANOM) is a graphical procedure used to quantify differences among treatment groups in a variety of experimental design and observational study situations. The ANOM decision chart allows one to easily draw conclusions and interpret results with respect to both statistical and practical significance. It is an excellent choice for multiple comparisons of means, rates, or proportions and can be used with both balanced and unbalanced data. Key advances in ANOM procedures that have appeared only in technical journals during the last 20 years are included in this first comprehensive modern treatment of the ANOM containing all of the needed information for practitioners to understand and apply ANOM.This book contains examples from a wide variety of fields adapted from real-world applications and data with easy-to-follow, step-by-step instructions. It is front loaded, so potential ANOM users can find solutions to standard problems in the first five chapters. An appendix contains several SAS® examples showing the system's ANOM capabilities and how SAS was used to produce selected ANOM decision charts in the book.Given these features, the lack of any other book on ANOM, and the recent inclusion of ANOM in SAS, this book will be a welcome addition to practitioners' and statisticians' bookshelves, where it will serve both as a primer and reference. N° de réf. du vendeur LU-9780898715927
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