Statistical Methods in Engineering and Manufacturing [Hardcover]

John E. Brown (Author)

Product Details

• Hardcover: 269 pages
• Publisher: Amer Society for Quality; First edition (February 1990)
• Language: English
• ISBN-10: 0873890779
• ISBN-13: 978-0873890779
• Product Dimensions: 10 x 7.2 x 1 inches
• Shipping Weight: 1.6 pounds (View shipping rates and policies)
• Average Customer Review: 2.5 out of 5 stars  See all reviews (2 customer reviews)
• Amazon Best Sellers Rank: #4,144,981 in Books (See Top 100 in Books)

More About the Author

Discover books, learn about writers, read author blogs, and more.

Customer Reviews

Most Helpful Customer Reviews

24 of 24 people found the following review helpful:

1.0 out of 5 stars poorly written and very cookbookish, February 9, 2008

By 

Michael R. Chernick "statman31147" (Holland PA) - See all my reviews
(REAL NAME)   

This review is from: Statistical Methods in Engineering and Manufacturing (Hardcover)

I reviewed this book for Technometrics in 1991. I would not recommend it for anyone! It is a cookbook of techniques that were selected by the author because he viewed them as useful in engineering or manufacturing. Almost no attention is given to the fundamental concepts and theory underlying the techniques.
Probability distributions are introduced without motivation giving the readers the misimpression that statistics is simply a set of tools to systematically apply. All the student needs to do is learn how to read a given set of statistical tables. This is a terrible impression to give in a first course and it makes for a very dry and boring course!

Analysis of variance is given some treatment in chapter 9 on experimental designs but the important topic of robust designs that had emerged in the 1980s specifically for manufacturing processes inspired by the work of Taguchi is not even mentioned.

Another problem with the book is the order in which topics are presented. Rather than being the 5th chapter, Chapter 5 on data gathering and problem solving should come first to motivate the methods and lead in to a discussion of probability distributions. Furthermore moments such as the skewness and kurtosis are discussed with reference to the Normal distribution before any formal presentation of the distribution and its properties. Sequential test procedures are thrown out to the student before even defining what a formal statistical hypothesis test is. Earlier classic books such as Bowker and Lieberman (1972) "Engineering Statistics" 2nd Edition or the two volumes of Johnson and Leone (1977)"Statistics and Experimental Design in Engineering and Physical Sciences" serve the students much better even if they do not have a strong background in mathematics.

Other problems with the book include vague definitions of such terms as central tendency, variance, skewness and kurtosis. Distributions such as the Normal distribution are referred to without a formal definition. Probability density functions are introduced without development of any probability concepts. There is a very poor description of the binomial distribution and its relationship to the binomial expansion.

In Chapter 2 operating characteristic curves are introduced but there is no discussion of power of tests. Hypothesis testing and type I and type II error probabilties are deferred to Chapter 8. In short this is book without foundation and will be very confusing to the audience it professes to teach. It can be used as a cookbook for those who want to run statistical procedures without any basic understanding, a very dangerous venture.

I have many more examples of specific problems with the book. If you want to see the details, go to the library and read my review on page 356 of Volume 33 of Technometrics (the August 1991 issue).

1 of 2 people found the following review helpful:

4.0 out of 5 stars Former Student, September 1, 2005

By 

Edward W. Poate "Wes" (Bay Area, CA) - See all my reviews
(REAL NAME)   

This review is from: Statistical Methods in Engineering and Manufacturing (Hardcover)

I used this text for one of my Stats classes (taught by John Brown). This book is a good basic book that makes stats more understandable than the usual Box, Hunter, & Hunter and the like (which I also use). It is written for a beginner who has limited background and wants to grasp the basics. It's clear and concise with solved problems. I use it as a reference for engineers who are just getting their feet wet in data analysis.