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Probability, Statistics, and Reliability for Engineers and Scientists, Second Edition
 
 
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Probability, Statistics, and Reliability for Engineers and Scientists, Second Edition [Hardcover]

Bilal M. Ayyub (Author), Richard H. McCuen (Author)
4.1 out of 5 stars  See all reviews (11 customer reviews)

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Probability, Statistics, and Reliability for Engineers and Scientists, Third Edition Probability, Statistics, and Reliability for Engineers and Scientists, Third Edition
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Book Description

1584882867 978-1584882862 June 26, 2002 2
Virtually every engineer and scientist needs to be able to collect, analyze, interpret, and properly use vast arrays of data. This means acquiring a solid foundation in the methods of data analysis and synthesis. Understanding the theoretical aspects is important, but learning to properly apply the theory to real-world problems is essential.

The second edition of this bestselling text introduces probability, statistics, reliability, and risk methods with an ideal balance of theory and applications. Clearly written and firmly focused on the practical use of these methods, it places increased emphasis on simulation, particularly as a modeling tool, applying it progressively with projects that continue in each chapter. It also features expanded discussions of the analysis of variance including single- and two-factor analyses and a thorough treatment of Monte Carlo simulation. The authors clearly establish the limitations, advantages, and disadvantages of each method, but also show that data analysis is a continuum rather than the isolated application of different methods.

Probability, Statistics, and Reliability for Engineers and Scientists, Second Edition, was designed as both a reference and as a textbook, and it serves each purpose well. Ultimately, readers will find its content of great value in problem solving and decision making, particularly in practical applications.

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Product Details

  • Hardcover: 656 pages
  • Publisher: Chapman and Hall/CRC; 2 edition (June 26, 2002)
  • Language: English
  • ISBN-10: 1584882867
  • ISBN-13: 978-1584882862
  • Product Dimensions: 9.6 x 6.2 x 1.6 inches
  • Shipping Weight: 2.4 pounds (View shipping rates and policies)
  • Average Customer Review: 4.1 out of 5 stars  See all reviews (11 customer reviews)
  • Amazon Best Sellers Rank: #699,771 in Books (See Top 100 in Books)

More About the Author

Bilal M. Ayyub is a professor of civil and environmental engineering at the University of Maryland, College Park, and the director of the Center for Technology and Systems Management (CTSM) at the A. James Clark School of Engineering. Ayyub has been at the University of Maryland since 1983. He is a leading authority in the areas of risk analysis, uncertainty modeling, decision analysis, and systems engineering. Ayyub is also the president of BMA Engineering, Inc., a Bethesda, Maryland-based engineering consulting firm that works with infrastructure and defense systems.

Ayyub is a multiple recipient of the ASNE Jimmie Hamilton Award for the best papers in the Naval Engineers Journal in 1985, 1992, 2000 and 2003. Also, he received the ASCE Outstanding Research Oriented Paper in the Journal of Water Resources Planning and Management for 1987, the ASCE Edmund Friedman Award in 1989, the ASCE Walter Huber Research Prize in 1997, and the K. S. Fu Award of NAFIPS in 1995. He received the Department of the Army Public Service Award in 2007 for leading the development of the risk model for the hurricane protection system of New Orleans. Ayyub was appointed to many national committees and investigation boards including most recently on the working group on higher education of the transition team of Maryland Governor Martin O'Malley, 2006-07, the working group on homeland security of the transition team of Maryland Governor Martin O'Malley, 2006-07, and the Committee for Assessment of the Bureau of Reclamation's Security Program, Board on Infrastructure and the Constructed Environment, National Research Council of the National Academies, 2006-08. He was appointed to the Maryland Governor's Commission on Middle Eastern American Affairs, and on the Board of Advisors of the ASCE Council on Disaster Risk Management(CDRM). Presently, he chairs the CDRM Vulnerability and Risk Committee. He has delivered many invited talks at leading national and international organizations including most recently a distinguished lecture to the Brazilian Research Agency, the Department of Homeland Security, Naval War College for the Chief of Naval Operations, the Army Corps of Engineers, and the Australian National Marine Safety Committee.

Ayyub is the author and co-author of more than 550 publications in journals and conference proceedings, and reports. Among the publications of Ayyub are more than 20 books.

 

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4 of 5 people found the following review helpful:
2.0 out of 5 stars Needs more meat, July 20, 2006
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This review is from: Probability, Statistics, and Reliability for Engineers and Scientists, Second Edition (Hardcover)
I teach this material myself and I don't feel the authors met there objectives of a practical, useful introduction to the topics of probability, statistics, and reliability. This book would be difficult to follow outside of a classroom, or without a good background in the course material already.

The introduction begins with a short essay on education and types of ignorance. I found the discussion quite interesting, and then the introduction jumps to the topic of simulation??? This strangle development flow is present throughout the book.

I often liked the beginning of sections, while not liking the development of details latter in the section / chapter. In many cases the details are at a high or advanced level with no transition or gradual ramping up from the introduction. So much material is covered that very few sections have complete coverage. Details are often missing, that is, more than this text will be required to solve common probability, statistics, and reliability problems.

I did find many of the examples interesting, and learned a few new things, again, because I already possessed a good background in the material. Each chapter also ends with interesting suggested computer simulation assignments.
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6 of 8 people found the following review helpful:
5.0 out of 5 stars From the authors, September 6, 1998
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.

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1 of 1 people found the following review helpful:
5.0 out of 5 stars Great Qualitative Text, December 2, 2005
This review is from: Probability, Statistics, and Reliability for Engineers and Scientists, Second Edition (Hardcover)
This is a great qualitative text written from a civil and environmental background. As a civil engineer taking a statistics course that was taught from a mechanical and industrial viewpoint, this book presented text and exapmles that came more naturally to me. Some of the qualitative aspects of the book could use improvement, and may make it difficult for use as a primary text book.
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Inside This Book (learn more)
First Sentence:
The processes of engineering analysis and design can be systematically performed within a systems framework. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
noncorrelated random variables, nonnormal probability distributions, conditional expectation method, midsquare method, cumulative mass function, nonlinear performance function, following performance function, nondefective units, basic random variables, extreme wave height, target reliability level, uniform variates, probabilistic characteristics, inverse transformation method, least significant range, standard error ratio, following density function, simulation cycles, rand function, being overtopped, multiple random variables, standardized partial regression coefficients, elastic section modulus, variation freedom squares, partial safety factors
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Monte Carlo, Stream Erosion Study, Structural Beam Study, Traffic Estimation Study, Water Evaporation Study, Very Large Radioactive Release, Piscataquis River, Random Mean Coefficient Distribution, Redo Problem, Failure Analysis, Table A-l, United States, Failure Survival, Reactions Due, Test of the Mean, The Bayesian, Treatment Block, Warehouse Construction, Distributions Two, Factor Level, Flow Output, Generated Stresses, Mean Wave, Piping Section, Stillwater Ratio
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