Probability, Statistics, and Reliability for Engineers and Scientists, Second Edition

Rating:
Summary: Systemic Context
Review: Ayyub provides an excellent systemic context for the exposition of reliability theory, especially as it relates to applications for decision-makers and decision-making. The mathematical basis of reliability in probability and statisitics is clearly presented and is suitable for engineering students and managers.

Rating:
Summary: From the authors
Review: In preparing this book, we strove to achieve the following educational objectives: (1) introducing probability, statistics, and reliability methods to engineering students and practicing engineers, (2) emphasizing the practical use of these methods, and (3) establishing the limitations, advantages, and disadvantages of the methods. Although, the book was developed with emphasis on engineering and technological problems, the methods can also be used to solve problems in other fields of sciences.

Problems that are commonly encountered by engineers require decision making under conditions of uncertainty. The uncertainty can be in the definition of a problem, the available information, the alternative solution methodologies and their results, and the random nature of the solution outcomes. Studies show that in the future engineers will need to solve more complex design problems with decisions made under conditions of limited resources, thus necessitating increased reliance on the proper treatment of uncertainty. Therefore, this book is intended to better prepare future engineers, as well as assist practicing engineers, in understanding the fundamentals of probability, statistics, and reliability methods, especially their applications, limitations, and potentials.

STRUCTURE, FORMAT, AND MAIN FEATURES

We have developed this book with a dual use in mind, as both a self-learning guidebook and as a required textbook for a course. In either case, the text has been designed to achieve important educational objectives.

The nine chapters of the book cover of the following subjects: (1) an introduction to the text that covers uncertainty types, decision analysis, and Taylor series expansion; (2) graphical analysis of data, and the computation of important characteristics of sample measurements and basic statistical characteristics; (3) the fundamentals of probability; (4) the joint behavior of random variables and the probabilistic characteristics of functions of random variables; (5) statistical analyses that include parameter estimation, hypothesis testing, confidence-interval estimation, sample-size determination, and probability-model selection; (6) curve fitting or model development based on data using regression analysis; (7) a formal presentation of Monte Carlo simulation; (8) reliability, risk, and decision analysis; and (9) the use of Bayesian methods in engineering. The book was designed for an introductory course in probability, statistics, and reliability with emphasis on applications. In developing the book, a set of educational outcomes as detailed in Chapter 1 motivated the structure and content of this text. Ultimately, serious readers will find the content of the book to be very useful in engineering problem solving and decision making. One of the most difficult to grasp aspects of probability and statistics is the concept of sampling variation. In engineering practice, an engineer typically has only one sample of data. It is important to recognize that the statistical results would be somewhat different if he or she had collected a different sample, even if that sample were equally likely to have occurred. Simulation is a means of demonstrating the sample-to-sample, or sampling, variation that can be expected. For this reason, we have incorporated a section on simulation at the end of each chapter (Chapters 1 to 6). Performing some simulations is one way of generating a better appreciation for sampling variation that is inherent in statistical problems presented in Chapters 1 to 6. Omitting the sections on simulation does not diminish a reader's understanding of the other sections or chapters. In each chapter of the book, computational examples are given in the individual sections of the chapter, with more detailed engineering applications given in a concluding section. Also, each chapter includes a set of exercise problems that cover the materials of the chapter. The problems were carefully designed to meet the needs of instructors in assigning homework and the readers in practicing the fundamental concepts. The book can be covered in one or two semesters depending the level of a course or the time allocated for topics covered in the book. The chapter sequence can be followed as a recommended sequence. However, if needed, instructors can choose a subset of the chapters for courses that do not permit a complete coverage of all chapters or a coverage that cannot follow the presented order. After completing Chapters 1, 2, and 3, the readers will have sufficient background to follow and understand the materials in the following tracks of chapters: Chapter 4; Chapters 5 and 6; Chapters 7 and 8; and Chapter 9 according to the indicated sequence.