- Hardcover: 174 pages
- Publisher: SPC PRESS (Statistical Process Control); 2 Revised edition (September 4, 2000)
- Language: English
- ISBN-10: 0945320531
- ISBN-13: 978-0945320531
- Product Dimensions: 0.8 x 6.2 x 9 inches
- Shipping Weight: 14.4 ounces (View shipping rates and policies)
- Average Customer Review: 4.5 out of 5 stars See all reviews (77 customer reviews)
- Amazon Best Sellers Rank: #82,479 in Books (See Top 100 in Books)
Enter your mobile number or email address below and we'll send you a link to download the free Kindle App. Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device required.
To get the free app, enter your mobile phone number.
Understanding Variation: The Key to Managing Chaos 2 Revised Edition
Use the Amazon App to scan ISBNs and compare prices.
Frequently bought together
Customers who bought this item also bought
About the Author
Dr. Donald J. Wheeler has been actively planting the seeds of transformation in companies and organizations around the world for over 25 years. His classes have been credited with being the essential element in turning companies around and taking them from red ink to black. In less spectacular ways his seminars have been the foundation for establishing learning cultures within many organizations in various industries. Unlike so many classes where the emphasis is upon techniques, Dr. Wheeler's classes go far beyond mere techniques to teaching the way of thinking needed to use those techniques effectively. He has worked with over 250 companies in chemical processing, health care, medical equipment, information technology, steel and aluminum production, agribusiness, food production and processing, electronics, pulp and paper processing, automotive suppliers, government agencies, and banking. Dr. Wheeler has taught over 1000 seminars in the USA, Canada, Mexico, England, Scotland, Ireland, Wales, Norway, Sweden, Finland, Germany, Belgium, Switzerland, Portugal, South Africa, Brazil and Malaysia. Over 60,000 students from the US and 32 countries on five continents have attended his seminars, which are held in Knoxville, Tennessee. Marketing research shows that word of mouth advertising brings in the majority of these students. We love it when our clients and students tell their friends and colleagues how good Dr. Wheeler's classes are! Along with his acclaimed seminars, Dr. Wheeler has also authored or coauthored twenty books which collectively form the definitive library for Discovery through Data Analysis. His books are being used throughout the US and in over 41 countries around the world. Dr. Wheeler has M.S. and Ph.D. degrees in Statistics from Southern Methodist University. He taught at the University of Tennessee for 12 years where he was an Associate Professor of Statistics. He is a Fellow both the American Statistical Association and the American Society for Quality, and he was an associate of Dr. W. Edwards Deming until his death in 1993. In short, Dr. Wheeler is the internationally recognized expert on Data Analysis and SPC. He has the knowledge, the experience, and the ability to communicate that knowledge and experience to others. For more information on Dr. Wheeler's books and seminars, contact SPC Press at 800-545-8602.
Browse award-winning titles. See more
If you are a seller for this product, would you like to suggest updates through seller support?
Top Customer Reviews
As a young boy in Tennessee, I sometimes uncovered "white lightning" (moonshine whiskey) hidden in forests. MIght his East Tennessee roots give Wheeler his rare sense of humor and fascination with how data and KPI's can be used to "cheat?"
This book is very rich in actual examples of data being used to mislead as well as KPI's which actually promote THE OPPOSITE behavior intended.
Wheeler takes the reader through multiple "cycles of learning" in this short read which is easily completed in under 2 hours on a flight. But be warned; once you read this book you will want to reread it and apply the lessons many times.
Are your processes "predictable" or are they "unpredictable?" With his jargon free, reader friendly style, Wheeler explains clearly 3 kinds of "Voice of the Customer" specifications, as well as sharing multiple examples and pitfalls which leaders make converting data into knowledge.
If you suffer from "rare" but important defects, be sure to read the next to last chapter. Brilliant!
The cases on pages 86 and 131 will inspire you to gain new insights building on the easily understandable histograms.
A must read for any Lean Six Sigma Executive, Sponsor or Belt. I buy this book in boxes of 10; I often find my colleagues and contacts asking to have my copy!
Excuse me. What are you saying? Are you saying that one upward blip can be extrapolated into a trend? Are you saying that because we flipped a coin 3 times and got heads (unemployment going down), and now we got a tail (unemployment going up) that our coin is defective? Are you saying that because temperatures were warmer than usual last week that we won't have winter?
One data point does not make a trend. We can't say the recovery is soft unless we know what the normal variation is on the out-of-work claims from week to week. Any result from week to week is going to be up or down (like heads or tails). Just because it goes up doesn't mean that a trend has reversed, when we didn't have a significant trend in the first place. 3 weeks of claims going down, analogous to coin flipping, could happen 1 in 8 times. The chance of it going down a fourth time is 1 in 16, unless there's a change in the system that creates unemployment claims (or better, creates jobs). Until we get to the odds of 1 in 64 (6 weeks in a row in the same direction--or some say, 1 in 256 is less risky for identifying a false trend) we can't say that we had an unemployment trend at all.
Please, Mr/Ms Economist and Mr/Ms Journalist, don't get confused and become Chicken Little thinking the economic sky is falling based on one piece of data that was going to show up normally. Read Wheeler's book to better understand all this.