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This text introduces a variety of standard statistical methods applicable to reliability data analysis. It is aimed at the non-specialist or manager and as such is primarily an applications guide. Methods addressed include analysis of variance, confidence interval estimation, goodness-of-fit tests, Weibull plotting, sampling inspection and regression and covariance analysis. Examples cover use of both parametric and nonparametric methods. (Author).
This practical introduction to the analysis of data collected from reliability studies offers clear, detailed explanations of the best and most up-to-date techniques available. Topics include survival analysis with covariates, the assessment of systems performance, reliability growth models, dependency (which encompasses both engineering and statistical approaches), and practical aspects of analysis. A wealth of interesting case studies appear throughout the text, lending "real-world" examples to the more theoretical discussions. Throughout, the authors stress the need for investigators to understand the background and nature of their data if they are to select the most appropriate analysis method. They also provide in-depth treatments of the mathematical and statistical bases underlying each technique. Accessible and comprehensive, the book will be welcomed by students, professionals, and statisticians who are interested in the practical aspects of reliability data analysis.
An authoritative guide to the most recent advances in statistical methods for quantifying reliability Statistical Methods for Reliability Data, Second Edition (SMRD2) is an essential guide to the most widely used and recently developed statistical methods for reliability data analysis and reliability test planning. Written by three experts in the area, SMRD2 updates and extends the long- established statistical techniques and shows how to apply powerful graphical, numerical, and simulation-based methods to a range of applications in reliability. SMRD2 is a comprehensive resource that describes maximum likelihood and Bayesian methods for solving practical problems that arise in product reliability and similar areas of application. SMRD2 illustrates methods with numerous applications and all the data sets are available on the book’s website. Also, SMRD2 contains an extensive collection of exercises that will enhance its use as a course textbook. The SMRD2's website contains valuable resources, including R packages, Stan model codes, presentation slides, technical notes, information about commercial software for reliability data analysis, and csv files for the 93 data sets used in the book's examples and exercises. The importance of statistical methods in the area of engineering reliability continues to grow and SMRD2 offers an updated guide for, exploring, modeling, and drawing conclusions from reliability data. SMRD2 features: Contains a wealth of information on modern methods and techniques for reliability data analysis Offers discussions on the practical problem-solving power of various Bayesian inference methods Provides examples of Bayesian data analysis performed using the R interface to the Stan system based on Stan models that are available on the book's website Includes helpful technical-problem and data-analysis exercise sets at the end of every chapter Presents illustrative computer graphics that highlight data, results of analyses, and technical concepts Written for engineers and statisticians in industry and academia, Statistical Methods for Reliability Data, Second Edition offers an authoritative guide to this important topic.
Software Reliability reviews some fundamental issues of software reliability as well as the techniques, models, and metrics used to predict the reliability of software. Topics covered include fault avoidance, fault removal, and fault tolerance, along with statistical methods for the objective assessment of predictive accuracy. Development cost models and life-cycle cost models are also discussed. This book is divided into eight sections and begins with a chapter on adaptive modeling used to predict software reliability, followed by a discussion on failure rate in software reliability growth models. The next chapter deals with methods for predicting and estimating software reliability, with emphasis on their strengths and weaknesses. The reader is methodically introduced to formal inspection in software development; the effects of product design, program structure, development methods, and the environments of product testing and use on product reliability; and types of software metrics in relation to reliability. The remaining chapters explore the ways in which software engineers have sought to achieve software reliability through testing; problems and standards in software reliability data collection; and applications of time series models to software reliability analysis. This monograph will be of interest to software engineers and designers.
This technical report reviews the use of statistics in art conservation research. Its aim is to examine how statistical analyses have been handled in published conservation research studies and to suggest alternative approaches. All components of data analysis—including experimental design, data organization, and statistical techniques—are evaluated.