Statistical Intervals: A Guide for Practitioners and Researchers (2nd Edition)

In certain situations, a researcher may need interval rather than point estimates for the parameter of interest (e.g., mean, standard deviation, proportion, or regression weights).This scenario often arises in industrial applications of statistics, such as reliability engineering, where intervals are needed for prediction of a condition, such as product lifetime failure.Traditional point estimate procedures are well covered in textbooks, while interval estimates are only touched upon mostly as an additional inference procedure.Therefore, researchers who mainly rely on statistical intervals may find the materials in applied statistics books inadequate.Statistical Intervals: A Guide for Practitioners and Researchers (2nd Edition) attempts to fill this gap using the statistical package R.The book has 18 chapters and ten technical appendices.The first ten chapters present less mathematically and computationally sophisticated methods for obtaining statistical intervals, followed by a chapter of case studies that demonstrates the application of those methods.Chapters 12-17 (which are new to the second edition of the book) present more advanced materials, followed by the last chapter on case studies.Each chapter ends with annotated bibliographic notes.There are no exercises, but the case study chapters can be used to practice the methods if the reader intends to.The statistical language R is used to demonstrate calculation and computation.The authors have bundled the necessary functions in the package StatInt, which can be downloaded from the book's companion website (which also hosts the data sets.)The authors introduce the concepts of uncertainty, inference, and prediction in Chapter 1, Introduction, Basic Concepts, and Assumptions.Throughout, "uncertainty" and how it is expressed through statistical intervals is elaborated.Different types of intervals covered in the book (confidence intervals, tolerance intervals, and prediction intervals) are discussed in this chapter.Furthermore, the authors distinguish between enumerative and analytic studies (see Deming 1975 for an original discussion of these concepts).In this chapter, the authors present foundational concepts such as assumptions underlying the data, sampling methods, study planning, and interpretation of interval estimates.Chapter 2, Overview

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