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Paperback Engineering Statistics Demystified Book

ISBN: 0071462724

ISBN13: 9780071462723

Engineering Statistics Demystified

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Book Overview

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Clueless? Feel Like a Dummy? Get Demystified

This versatile reference offers solid coverage of the basics oftraditional engineering statistics and also incorporates examplesfrom the most popular statistical software programs, making it equally...

Customer Reviews

2 ratings

Very Good Book

It is a very good book. Remember, engineering statistics is different from an ordinary statistics book in that its goal is to show you how to apply the subject in practical ways (ie using Excel, Mapel, other software programs and in solving real world problems). To this end the book does a good job. I would have given it 5 stars but in my opinion there should've been more detailed photos of software inputs. The book describes inputs but it is always much clearer when you can see it. However, it is a very good book.

Modern take on engineering stats

It's an outstanding way to learn or brush up on basic statistics. I love how the numerous examples -- the book is really a collection of examples -- use Excel, Minitab, SAS, SPSS, Statistix and Maple software for solutions. In many cases the author shows how the solve the example using two or three of the software packages. He also provides the traditional paper-and-pencil methods, but emphasizes this is really only to ensure the reader understands the material. The first chapter starts with a 2-paragraph introduction that includes information on how to get trial versions of the software (and an admonition that Excel should already be on your computer). Then, with no further fanfare, the first example problem is given and solved. It's great that the meat of the material is immediately and practically provided. Each chapter ends with a summary and series of exercises. The book concludes with "final examinations." But then there are about 90 pages of solutions to the exercises and exams. A short bibliography and complete index finish the book. Chapters cover the following topics: - Treatment of data: graphical displays, descriptive measures, relative standing - Probability: sample space, Axioms, elementary theorems, conditional probability - Probability distributions for discrete random variables - Probability densities for continuous random variables - Sampling distributions - Inferences concerning means - Inferences concerning variances - Inferences concerning proportions Examples are relevant to engineering; many relate to the digital world such as defects on CDs, sampling strategies for MP3 players, etc. Quoting: "Engineers for the EPA have found that fluoride in a large city's water supply have concentrations that follow ..." The only deficiency in the book for me is that it does not explain how a certain probability distribution is determined. It does go through several different distribution families (normal, uniform, log-normal, gamma, beta, Weibull), describes their characteristics, shows graphs of the distributions, and explains how to use the software to utilize them. But I remain mystified as to how to decide if a particular population fits a gamma, beta, exponential or other type of distribution. Completing the quote at the end of the previous paragraph: "a log-normal distribution with parameters alpha = 3.2 and beta = 1. What is the probability that the concentration exceeds 8 ppm?" But how did the engineers determine that log-normal was the best distribution to use?
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