Thoroughly revised and reorganized, the fourth edition presents in-depth coverage of the theory and methods of the most widely used nonparametric procedures in statistical analysis and offers example applications appropriate for all areas of the social, behavioral, and life sciences. The book presents new material on the quantiles, the calculation of exact and simulated power, multiple comparisons, additional goodness-of-fit tests, methods of analysis of count data, and modern computer applications using MINITAB, SAS, and STATXACT. It includes tabular guides for simplified applications of tests and finding P values and confidence interval estimates.

Nonparametric Statistical Inference, Fourth Edition: Revised and Expanded (Statistics: A Series of Textbooks and Monographs)

Science & Math

Gibbons, Jean Dickinson

Chakraborti, Subhabrata

Mathematics

CRC-Press

A unique approach to understanding the foundations of statistical quality control with a focus on the latest developments in nonparametric control charting methodologies Statistical Process Control (SPC) methods have a long and successful history and have revolutionized many facets of industrial production around the world. This book addresses recent developments in statistical process control bringing the modern use of computers and simulations along with theory within the reach of both the researchers and practitioners. The emphasis is on the burgeoning field of nonparametric SPC (NSPC) and the many new methodologies developed by researchers worldwide that are revolutionizing SPC. Over the last several years research in SPC, particularly on control charts, has seen phenomenal growth. Control charts are no longer confined to manufacturing and are now applied for process control and monitoring in a wide array of applications, from education, to environmental monitoring, to disease mapping, to crime prevention. This book addresses quality control methodology, especially control charts, from a statistician’s viewpoint, striking a careful balance between theory and practice. Although the focus is on the newer nonparametric control charts, the reader is first introduced to the main classes of the parametric control charts and the associated theory, so that the proper foundational background can be laid. <ul>
<li>Reviews basic SPC theory and terminology, the different types of control charts, control chart design, sample size, sampling frequency, control limits, and more</li> <li>Focuses on the distribution-free (nonparametric) charts for the cases in which the underlying process distribution is unknown</li> <li>Provides guidance on control chart selection, choosing control limits and other quality related matters, along with all relevant formulas and tables</li> <li>Uses computer simulations and graphics to illustrate concepts and explore the latest research in SPC</li> </ul>
Offering a uniquely balanced presentation of both theory and practice, Nonparametric Methods for Statistical Quality Control is a vital resource for students, interested practitioners, researchers, and anyone with an appropriate background in statistics interested in learning about the foundations of SPC and latest developments in NSPC.

Nonparametric Statistical Process Control

Graham, Marien

wiley

Product Description 
Praise for previous editions:\n"… a classic with a long history." – Statistical Papers\n"The fact that the first edition of this book was published in 1971 … [is] testimony to the book’s success over a long period." – ISI Short Book Reviews\n"… one of the best books available for a theory course on nonparametric statistics. … very well written and organized … recommended for teachers and graduate students." – Biometrics\n"… There is no competitor for this book and its comprehensive development and application of nonparametric methods. Users of one of the earlier editions should certainly consider upgrading to this new edition." – Technometrics\n"… Useful to students and research workers … a good textbook for a beginning graduate-level course in nonparametric statistics." – Journal of the American Statistical Association 
Since its first publication in 1971, Nonparametric Statistical Inference has been widely regarded as the source for learning about nonparametrics. The Sixth Edition carries on this tradition and incorporates computer solutions based on R. \nFeatures \nCovers the most commonly used nonparametric procedures\nStates the assumptions, develops the theory behind the procedures, and illustrates the techniques using realistic examples from the social, behavioral, and life sciences\nPresents tests of hypotheses, confidence-interval estimation, sample size determination, power, and comparisons of competing procedures\nIncludes an Appendix of user-friendly tables needed for solutions to all data-oriented examples\nGives examples of computer applications based on R, MINITAB, STATXACT, and SAS\nLists over 100 new references\nNonparametric Statistical Inference, Sixth Edition, has been thoroughly revised and rewritten to make it more readable and reader-friendly. All of the R solutions are new and make this book much more useful for applications in modern times. It has been updated throughout and contains 100 new citations, including some of the most recent, to make it more current and useful for researchers. 
 Review 
“… a classic with a long history.” ― Statistical Papers 
“The fact that the first edition of this book was published in 1971 … [is]ntestimony to the book’s success over a long period.” ― ISI Short Book Reviews 
“ … one of the best books available for a theory course on nonparametric statistics. … very well written and organized … recommended for teachers and graduate students.” – Biometrics 
“… There is no competitor for this book and its comprehensive development and application of nonparametric methods. Users of one of the earlier editions should certainly consider upgrading to this new edition.” ―Technometrics 
“… Useful to students and research workers … a good textbook for a beginning graduate-level course in nonparametric statistics.” ―Journal of the American Statistical Association 
 About the Author 
Jean Dickinson Gibbons is Russell Professor Emerita of Applied Statistics at the University of Alabama, where she also served as Chair for 20 years. She is a life member of the American Statistical Association, serving three terms on their Board of Directors; she was elected a Fellow in 1972. She earned the B.A. (1958) and M.A. (1959) in mathematics from Duke University and the Ph.D. (1962) in statistics from Virginia Tech, which recently named their graduate program after her. In addition to Alabama, she taught at the Wharton School of the University of Pennsylvania, the University of Cincinnati and Mercer University and offered short courses for the U.S. Army, the Naval Postgraduate School and the American Statistical Association. She currently lives in Vero Beach, Florida, where she is a peer leader in the Fielden Institute for Lifelong Learning at Indian River State College.\nSubhabrata Chakraborti is Professor of Statistics and Morrow Faculty Fellow at the University of Alabama. He is a Fellow of the American Statistical A

Nonparametric Statistical Inference (Statistics: A Series of Textbooks and Monographs)

Reference

Chapman and Hall/CRC

Proven Material for a Course on the Introduction to the Theory and/or on the Applications of Classical Nonparametric Methods Since its first publication in 1971, Nonparametric Statistical Inference has been widely regarded as the source for learning about nonparametric statistics. The fifth edition carries on this tradition while thoroughly revising at least 50 percent of the material. New to the Fifth Edition <ul>
<li>Updated and revised contents based on recent journal articles in the literature</li> <li>A new section in the chapter on goodness-of-fit tests </li> <li>A new chapter that offers practical guidance on how to choose among the various nonparametric procedures covered </li> <li>Additional problems and examples </li> <li>Improved computer figures </li> </ul> This classic, best-selling statistics book continues to cover the most commonly used nonparametric procedures. The authors carefully state the assumptions, develop the theory behind the procedures, and illustrate the techniques using realistic research examples from the social, behavioral, and life sciences. For most procedures, they present the tests of hypotheses, confidence interval estimation, sample size determination, power, and comparisons of other relevant procedures. The text also gives examples of computer applications based on Minitab, SAS, and StatXact and compares these examples with corresponding hand calculations. The appendix includes a collection of tables required for solving the data-oriented problems. Nonparametric Statistical Inference, Fifth Edition provides in-depth yet accessible coverage of the theory and methods of nonparametric statistical inference procedures. It takes a practical approach that draws on scores of examples and problems and minimizes the theorem-proof format. Jean Dickinson Gibbons was recently interviewed regarding her generous pledge to Virginia Tech.

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Books by Chakraborti, Subhabrata

See the best price to sell, buy, or rent books by Chakraborti, Subhabrata. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Nonparametric Statistical Inference, Fourth Edition: Revised and Expanded (Statistics: A Series of Textbooks and Monographs)

Nonparametric Statistical Process Control

Nonparametric Statistical Inference (Statistics: A Series of Textbooks and Monographs)

Nonparametric Statistical Inference (Statistics: A Series of Textbooks and Monographs)