Statistical Intervals: A Guide for Practitioners and Researchers (Wiley Series in Probability and Statistics)
by: William Q. Meeker (Author),Gerald J. Hahn(Author),Luis A. Escobar(Author)&0more
Publisher:Wiley
Publication Date: 6 Jun. 2017
Language:English
Print Length:648 pages
ISBN-10:0471687170
ISBN-13:9780471687177
Book Description
Describes statistical intervals to quantify sampling uncertainty,focusing on key application needs and recently developed methodology in an easy-to-apply formatStatistical intervals provide invaluable tools for quantifying sampling uncertainty. The widely hailed first edition, published in 1991, described the use and construction of the most important statistical intervals. Particular emphasis was given to intervals―such as prediction intervals, tolerance intervals and confidence intervals on distribution quantiles―frequently needed in practice, but often neglected in introductory courses.Vastly improved computer capabilities over the past 25 years have resulted in an explosion of the tools readily available to analysts. This second edition―more than double the size of the first―adds these new methods in an easy-to-apply format. In addition to extensive updating of the original chapters, the second edition includes new chapters on:Likelihood-based statistical intervalsNonparametric bootstrap intervalsParametric bootstrap and other simulation-based intervalsAn introduction to Bayesian intervalsBayesian intervals for the popular binomial, Poisson and normal distributionsStatistical intervals for Bayesian hierarchical modelsAdvanced case studies, further illustrating the use of the newly described methodsNew technical appendices provide justification of the methods and pathways to extensions and further applications. A webpage directs readers to current readily accessible computer software and other useful information.Statistical Intervals: A Guide for Practitioners and Researchers, Second Edition is an up-to-date working guide and reference for all who analyze data, allowing them to quantify the uncertainty in their results using statistical intervals.
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