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.

'The book provides a well-written, comprehensive discussion of the analysis of means applied to almost all standard statistical methods.' William J. Wilson, Professor of Statistics, University of North Florida 'The book is a very practical comprehensive guide to the ANOM procedure. It has widespread application and is written at a level that can be comprehended by those who do not have a background in statistics. The ANOM procedures presented in the book provide the reader a means of communicating data to management, industry regulators, and peers in simple, graphical terms. The procedures combine the power of statistics with the simplicity of basic plotting techniques.' Sheri L. Meredith, Senior Quality Engineer, Vistakon, Division of Johnson & Johnson Vision Care, Inc., Jacksonville, Florida 'This book provides an excellent introduction to ANOM, and it should be part of every statistician's library. It is well written and covers a wide range of methods ... In addition to the lucid presentation of the different types of analyses, the authors also provide excellent explanations of statistical concepts, as they are needed.' Gudmund R. Iverson, MAA Reviews

• PrefaceIntroductionChapter 1: One-Factor Balanced StudiesChapter 2: One-Factor Unbalanced StudiesChapter 3: Testing for Equal VariancesChapter 4: Complete Multi-Factor StudiesChapter 5: Incomplete Multi-Factor StudiesChapter 6: Axial Mixture DesignsChapter 7: Heteroscedastic DataChapter 8: Distribution-Free TechniquesAppendix A: FiguresAppendix B: TablesAppendix C: SAS ExamplesReferencesIndex.

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.

'The book provides a well-written, comprehensive discussion of the analysis of means applied to almost all standard statistical methods.' William J. Wilson, Professor of Statistics, University of North Florida 'The book is a very practical comprehensive guide to the ANOM procedure. It has widespread application and is written at a level that can be comprehended by those who do not have a background in statistics. The ANOM procedures presented in the book provide the reader a means of communicating data to management, industry regulators, and peers in simple, graphical terms. The procedures combine the power of statistics with the simplicity of basic plotting techniques.' Sheri L. Meredith, Senior Quality Engineer, Vistakon, Division of Johnson & Johnson Vision Care, Inc., Jacksonville, Florida 'This book provides an excellent introduction to ANOM, and it should be part of every statistician's library. It is well written and covers a wide range of methods ... In addition to the lucid presentation of the different types of analyses, the authors also provide excellent explanations of statistical concepts, as they are needed.' Gudmund R. Iverson, MAA Reviews

• PrefaceIntroductionChapter 1: One-Factor Balanced StudiesChapter 2: One-Factor Unbalanced StudiesChapter 3: Testing for Equal VariancesChapter 4: Complete Multi-Factor StudiesChapter 5: Incomplete Multi-Factor StudiesChapter 6: Axial Mixture DesignsChapter 7: Heteroscedastic DataChapter 8: Distribution-Free TechniquesAppendix A: FiguresAppendix B: TablesAppendix C: SAS ExamplesReferencesIndex.

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.

'The book provides a well-written, comprehensive discussion of the analysis of means applied to almost all standard statistical methods.' William J. Wilson, Professor of Statistics, University of North Florida 'The book is a very practical comprehensive guide to the ANOM procedure. It has widespread application and is written at a level that can be comprehended by those who do not have a background in statistics. The ANOM procedures presented in the book provide the reader a means of communicating data to management, industry regulators, and peers in simple, graphical terms. The procedures combine the power of statistics with the simplicity of basic plotting techniques.' Sheri L. Meredith, Senior Quality Engineer, Vistakon, Division of Johnson & Johnson Vision Care, Inc., Jacksonville, Florida 'This book provides an excellent introduction to ANOM, and it should be part of every statistician's library. It is well written and covers a wide range of methods ... In addition to the lucid presentation of the different types of analyses, the authors also provide excellent explanations of statistical concepts, as they are needed.' Gudmund R. Iverson, MAA Reviews

• PrefaceIntroductionChapter 1: One-Factor Balanced StudiesChapter 2: One-Factor Unbalanced StudiesChapter 3: Testing for Equal VariancesChapter 4: Complete Multi-Factor StudiesChapter 5: Incomplete Multi-Factor StudiesChapter 6: Axial Mixture DesignsChapter 7: Heteroscedastic DataChapter 8: Distribution-Free TechniquesAppendix A: FiguresAppendix B: TablesAppendix C: SAS ExamplesReferencesIndex.