Ansell, J. I.; Phillips, M. J. Practical methods for reliability data analysis. (English) Zbl 0853.62075 Oxford Statistical Science Series. 14. Oxford: Clarendon Press. xvi, 240 p. (1994). As the name of the book indicates, the emphasis in this text is on practice. Since every practical problem is different from another practical problem, only a selection of such problems can be analyzed in a text such as the reviewed one. It is hoped then that the reader has a large enough sample of analyzed problems to be able to find one that is applicable to the particular practical problem that the reader encounters. The authors state in the Preface: “Part of the process of achieving the(se) goals of high reliability is the analysis of reliability data. Many reliability analyses require the use of statistical techniques to aid in the analysis, assessment, and prediction of the performance of equipment and systems. It is these problems which the book addresses.”In Chapter 1 the authors give a range of examples of practical reliability problems. They also provide in this chapter the necessary probability background for the rest of the text. In Chapter 2 they describe some common lifetime distributions and some common models of censoring. They also give in this chapter some details of the Kaplan-Meier nonparametric estimation of distributions of failure times. Furthermore, basic methods of statistical estimation and hypothesis testing are also given in Chapter 2. A not so common description of the Nelson-Altschuler estimator of the cumulative hazard function is also included in Chapter 2. The analysis of lifetimes with covariates is the subject of Chapter 3. The accelerated failure time model, the proportional hazards model, and the logistic model are some of the models described in Chapter 3.The basic ideas of coherent structures are described in Chapter 4. Included in this chapter are the studies of two kinds of failures, the study of the fault tree analysis, and the study of influence diagrams. Some models of repairable systems are described in Chapter 5. That is, the nonhomogeneous Poisson process and renewal processes are outlined. When the authors study multicomponent repairable systems, the study naturally leads to a discussion of Markovian and semi-Markovian models. In Chapter 6 they analyze the data that arise from the models of Chapter 5. For example, trend tests are described in this chapter.Various reliability growth models are critically reviewed in Chapter 7. Dependency analysis is outlined in Chapter 8, where several models for dependency are described. Some practical aspects of reliability data analysis are outlined in Chapter 9. Included in this chapter is a description of Tukey’s exploratory data analysis, which is applied to reliability data. The discussion in this chapter is accompanied by many illustrative graphs. Finally, in Chapter 10, the authors explore three case studies illustrating the types of problems faced by reliability engineers.The reviewer believes that practitioners of reliability data analysis will find this book very useful. Reviewer: M.Shaked (Tucson) Cited in 3 Documents MSC: 62N05 Reliability and life testing 62-01 Introductory exposition (textbooks, tutorial papers, etc.) pertaining to statistics Keywords:reliability; lifetime distributions; models of censoring; Kaplan-Meier nonparametric estimation; failure times; Nelson-Altschuler estimator; covariates; accelerated failure time model; proportional hazards model; logistic model; coherent structures; fault tree analysis; influence diagrams; models of repairable systems; nonhomogeneous Poisson process; renewal processes; semi-Markovian models; trend tests; reliability growth models; models for dependency; Tukey’s exploratory data analysis PDFBibTeX XMLCite \textit{J. I. Ansell} and \textit{M. J. Phillips}, Practical methods for reliability data analysis. Oxford: Clarendon Press (1994; Zbl 0853.62075)