Reliability: Probabilistic Models and Statistical Methods (Prentice-Hall International Series in Industrial and Systems Engineering) (Paperback)

by Lawrence M. Leemis (Author)

Editorial Reviews

Product Description
Covers both the Probabalistic models and Statistical methods used by reliability engineers. It contains explanations of how the mathematical models and results apply to engineering design and the analysis of lifetime data sets. Most applications are drawn from mechanical, civil or electrical engineering systems.

From the Publisher
An elementary introduction to the probabilistic models and statistical methods used by reliability engineers as applied to, for example, electrical or mechanical systems. Leemis offers explanations of how the mathematical models and results apply to engineering design and the analysis of lifetime data sets, with simple, supplementary proofs and derivations provided when necessary.

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Product Details

• Paperback: 288 pages
• Publisher: Prentice Hall (December 30, 1994)
• Language: English
• ISBN-10: 0137205171
• ISBN-13: 978-0137205172
• Product Dimensions: 9.1 x 6.9 x 0.8 inches
• Shipping Weight: 1.2 pounds (View shipping rates and policies)
• Average Customer Review: 5.0 out of 5 stars See all reviews (3 customer reviews)
• Amazon.com Sales Rank: #1,390,164 in Books (See Bestsellers in Books)

Customer Reviews

Most Helpful Customer Reviews

6 of 6 people found the following review helpful:

5.0 out of 5 stars Outstanding!, October 13, 1999

By A Customer

This is definitely the best text on Reliability Engineering that I've seen. Leemis really brings the material to life in a way that I have not seen replicated in the other texts that I have perused. For a first introduction to Reliability, I cannot think of a better text. The reader should have a solid foundation in mathematical statistics, however, before starting on this volume. An adequate resource for building this foundation is Larson and Marx's "Introduction to Mathematical Statistics". Especially make sure you understand the basics of maximum-likelihood, as Leemis emphasizes it in his derivations -- the more advanced stuff you'll learn about in his book, however.

As an aside, I have actually taken Leemis' class, and I can honestly say that I learned more about probability from his lectures and the text than I ever previously thought possible. Again, I highly recommend the text.

2 of 2 people found the following review helpful:

5.0 out of 5 stars The definitive introduction to reliability analysis, February 1, 2001

By	Edward Williams (Dearborn, Michigan, USA) - See all my reviews

This is THE seminal text on reliability analysis. The author writes with the same crystal clarity he uses to present material at technical conferences. The exercises are carefully graded to lead the diligent reader toward steadily deepening understanding of the material. All diagrams are clear, cogent, carefully annotated, and well keyed to accompanying text. The definition and explanations of cut sets are especially good, allowing the engineer or analyst to economically reduce a complex problem to a set of smaller, more mathematically tractable problems. Also, this work does an excellent job of ramping the reader's knowledge upward from the justifiably assumes prerequisite of basic statistics learned in one introductory class presumably having a calculus prerequisite.

1 of 2 people found the following review helpful:

5.0 out of 5 stars Excellent presentation of Reliability Math, February 4, 2000

By	E. Taylor (Mountian View, CA) - See all my reviews

I have to give it to this author, he has a very high assumption of math. If you are not a math wiz but can comprehend Calculus, this book is beyond outstanding. I will give the reader the necessary math methods for achieving you reliability analysis correctly. I spent alot of time going through these calcs and doing the proofs they are with out a dought right on the money. The boo is packed full of wonderful examples and methods. Kudos to the author.