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Modern Engineering Statistics [Hardcover]

Thomas P. Ryan
4.2 out of 5 stars  See all reviews (4 customer reviews)

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Book Description

September 28, 2007 0470081872 978-0470081877 1
An introductory perspective on statistical applications in the field of engineering

Modern Engineering Statistics presents state-of-the-art statistical methodology germane to engineering applications. With a nice blend of methodology and applications, this book provides and carefully explains the concepts necessary for students to fully grasp and appreciate contemporary statistical techniques in the context of engineering.

With almost thirty years of teaching experience, many of which were spent teaching engineering statistics courses, the author has successfully developed a book that displays modern statistical techniques and provides effective tools for student use. This book features:

  • Examples demonstrating the use of statistical thinking and methodology for practicing engineers

  • A large number of chapter exercises that provide the opportunity for readers to solve engineering-related problems, often using real data sets

  • Clear illustrations of the relationship between hypothesis tests and confidence intervals

  • Extensive use of Minitab and JMP to illustrate statistical analyses

The book is written in an engaging style that interconnects and builds on discussions, examples, and methods as readers progress from chapter to chapter. The assumptions on which the methodology is based are stated and tested in applications. Each chapter concludes with a summary highlighting the key points that are needed in order to advance in the text, as well as a list of references for further reading. Certain chapters that contain more than a few methods also provide end-of-chapter guidelines on the proper selection and use of those methods. Bridging the gap between statistics education and real-world applications, Modern Engineering Statistics is ideal for either a one- or two-semester course in engineering statistics.



Editorial Reviews

Review

"Overall this is an excellent book, which defines a broader mandate than many of its competing texts. By providing, clear, understandable discussion of the basics of statistics through to more advanced methods commonly used by engineers, this book is an essential reference for practitioners, and an ideal text for a two semester course introducing engineers to the power and utility of statistics." (The American Statistician, August 2008)

"In this book on modern engineering statistics, Ryan does an excellent job of providing the appropriate statistical concepts and tools using engineering resources.... Highly recommended. Lower- and upper-division undergraduates" (CHOICE, April 2008)

"This self-contained volume motivates an appreciation of statistical techniques within the context of engineering; many datasets that are used in the chapters and exercises are from engineering sources. This book is ideal for either a one- or two-semester course in engineering statistics." (Computing Reviews, April 2008)

From the Back Cover

An introductory perspective on statistical applications in the field of engineering

Modern Engineering Statistics presents state-of-the-art statistical methodology germane to engineering applications. With a nice blend of methodology and applications, this book provides and carefully explains the concepts necessary for students to fully grasp and appreciate contemporary statistical techniques in the context of engineering.

With almost thirty years of teaching experience, many of which were spent teaching engineering statistics courses, the author has successfully developed a book that displays modern statistical techniques and provides effective tools for student use. This book features:

  • Examples demonstrating the use of statistical thinking and methodology for practicing engineers

  • A large number of chapter exercises that provide the opportunity for readers to solve engineering-related problems, often using real data sets

  • Clear illustrations of the relationship between hypothesis tests and confidence intervals

  • Extensive use of Minitab and JMP to illustrate statistical analyses

The book is written in an engaging style that interconnects and builds on discussions, examples, and methods as readers progress from chapter to chapter. The assumptions on which the methodology is based are stated and tested in applications. Each chapter concludes with a summary highlighting the key points that are needed in order to advance in the text, as well as a list of references for further reading. Certain chapters that contain more than a few methods also provide end-of-chapter guidelines on the proper selection and use of those methods. Bridging the gap between statistics education and real-world applications, Modern Engineering Statistics is ideal for either a one- or two-semester course in engineering statistics.


Product Details

  • Hardcover: 736 pages
  • Publisher: Wiley-Interscience; 1 edition (September 28, 2007)
  • Language: English
  • ISBN-10: 0470081872
  • ISBN-13: 978-0470081877
  • Product Dimensions: 10 x 7.1 x 1.4 inches
  • Shipping Weight: 2.6 pounds (View shipping rates and policies)
  • Average Customer Review: 4.2 out of 5 stars  See all reviews (4 customer reviews)
  • Amazon Best Sellers Rank: #551,182 in Books (See Top 100 in Books)

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Customer Reviews

4.2 out of 5 stars
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3 of 3 people found the following review helpful
5.0 out of 5 stars Modern Eng Stats Review November 6, 2007
Format:Hardcover
An exceptionally well written book with many useful examples, case studies, and end of chapter exercises. Balances the theoretical aspect of statistics with real world examples. One of the few books that specifically covers the application of statistics for a manufacturing / engineering environment.

A very useful resource for anyone involved in Six Sigma, quality, or engineering in a manufacturing setting.

Although not touted as a Minitab resource / reference book there are plenty of worked examples that use Minitab, which I found to be an added bonus.
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2 of 2 people found the following review helpful
3.0 out of 5 stars Broad overview, not many details... May 25, 2010
Format:Hardcover
My viewpoint expressed is that of an EE needing to do a bit of reliability and lifetime testing. I think the book is fine at providing a sweeping overview of statistics, and I believe the author chose important and relevant and non-standard topics (bootstrapping, analysis of means as opposed to ANOVA, life testing, etc.) but he does not bother to go into much detail about most. He presents a lot of Minitab or JMP results instead of presenting the basic formulae. This may be wise, in the sense that more mistakes are likely to be made by a non-statistician implementing techniques from scatch rather than relying on the software to do it, but I find it somewhat unnerving to use techniques without getting a bit of a look at the mechanics (i.e. equations and formula) involved. The author refers a lot to online free e-handbooks for basic details, and I could not help think, if I wanted to go online to study this, why did I buy this book? Meeker and Escobar have written what (in my somewhat stats-uneducated opinion) looks like a fine book on reliability and lifetime testing but seems a bit too advanced for me in spots. I was hoping to use Ryan's book as a bridge, but it seems not very useful for this (not enough detail behind the methods whether life testing, bootstrapping, ANOM etc.). I think this is a fine lower level stats book, but for something like boostrapping I have learned a lot more from the 3rd edition of deGroot/Schervish (a general undergrad stat book) e.g. how to make a confidence interval for the IQR, or for ANOM from Ott's original process quality control book.
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2 of 3 people found the following review helpful
5.0 out of 5 stars another fine introductory book by Tom Ryan March 3, 2009
Format:Hardcover
I know Tom Ryan well. He and I both teach on the faculty at statistics.com. I have reviewed other books that he has written. He is an excellent teacher and always write very clearly and is thorough in his coverage of a topic. He is especially good at introductory statistics and he uses Minitab to work out examples in his texts as well a the SAS product JMP. This book is in line with the high quality of his experimental design book, his regression text and is text on quality control.

Statistics is a diverse science with applications in every discipline that has to deal with uncertainty. But terms like biostatistics, engineering statistics, and environmental statistics have come about because they each have special statistical tools that they use that other disciplines may not.

In biostatistics, survival curves, longitudinal data analysis, missing data analysis and categorical data analysis are especially important. In quality control, control charts, process control indices and tolerance intervals are important. In epidemiology case control and other observation studies are important. In economic statistics (econometrics) time series analysis is important. These are the reasons why instead of just a general introductory book in fields like biostatistics and engineering statistics specialized texts are needed.

There are several good texts for engineers but there are not many that are as current or encompassing as Ryan's text. The first 6 chapters are standard to any introductory course. He covers descriptive statistics, basic probability and the common important probability distributions, point estimation and confidence intervals and hypothesis testing. Then in chapter 7 he covers tolerance intervals and prediction intervals.
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0 of 1 people found the following review helpful
4.0 out of 5 stars It is good! September 21, 2013
Format:Hardcover|Verified Purchase
The book is i good condition with no scratch or writing on its page. But the only thing was it is price.
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