Statistical intervals : a guide for practitioners and researchers.

Includes bibliographical references and index.

Includes bibliographical references and index.

Statistical Intervals; Contents; Preface to Second Edition; Overview; Elaboration on New Methods; New Technical Appendices; Computer Software; More on Book's Webpage; Summary of Changes from First Edition; Preface to First Edition; Acknowledgments; About the Companion Website; Chapter 1 Introduction, Basic Concepts, and Assumptions; Objectives and Overview; 1.1 Statistical Inference; 1.2 Different Types of Statistical Intervals: An Overview; 1.3 The Assumption of Sample Data; 1.4 The Central Role of Practical Assumptions Concerning Representative Data; 1.5 Enumerative versus Analytic Studies. 1.5.1 Differentiating between Enumerative and Analytic Studies1.5.2 Statistical Inference for Analytic Studies; 1.5.3 Inferential versus Predictive Analyses; 1.6 Basic Assumptions for Inferences from Enumerative Studies; 1.6.1 Definition of the Target Population and Frame; 1.6.2 The Assumption of a Random Sample; 1.6.3 More Complicated Random Sampling Schemes; 1.7 Considerations in the Conduct of Analytic Studies; 1.7.1 Analytic Studies; 1.7.2 The Concept of Statistical Control; 1.7.3 Other Analytic Studies; 1.7.4 How to Proceed; 1.7.5 Planning and Conducting an Analytic Study. 1.8 Convenience and Judgment Samples1.9 Sampling People; 1.10 Infinite Population Assumptions; 1.11 Practical Assumptions: Overview; 1.12 Practical Assumptions: Further Example; 1.13 Planning the Study; 1.14 The Role of Statistical Distributions; 1.15 The Interpretation of Statistical Intervals; 1.16 Statistical Intervals and Big Data; 1.17 Comment Concerning Subsequent Discussion; BIBLIOGRAPHIC NOTES; Chapter 2 Overview of Different Types of Statistical Intervals; Objectives and Overview; 2.1 Choice of a Statistical Interval; 2.1.1 Purpose of the Interval; 2.1.2 Characteristic of Interest. 2.2 Confidence Intervals2.2.1 Confidence Interval for a Distribution Parameter; 2.2.2 Confidence Interval for a Distribution Quantile; 2.2.3 Confidence Interval for the Probability of Meeting Specifications; 2.2.4 One-Sided Confidence Bounds; 2.2.5 Interpretations of Confidence Intervals and Bounds; 2.3 Prediction Intervals; 2.3.1 Prediction Interval to Contain a Single Future Observation; 2.3.2 Prediction Interval to Contain All of m Future Observations; 2.3.3 Prediction Interval to Contain at Least k out of m Future Observations.

Describes statistical intervals to quantify sampling uncertainty,focusing on key application needs and recently developed methodology in an easy-to-apply format Statistical 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 intervals Nonparametric bootstrap intervals Parametric bootstrap and other simulation-based intervals An introduction to Bayesian intervals Bayesian intervals for the popular binomial, Poisson and normal distributions Statistical intervals for Bayesian hierarchical models Advanced case studies, further illustrating the use of the newly described methods New 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.