Item description for Fuzzy Statistics by James J. Buckley...
This monograph introduces elementary fuzzy statistics based on crisp (non-fuzzy) data. In the introductory chapters the book presents a very readable survey of fuzzy sets including fuzzy arithmetic and fuzzy functions. The book develops fuzzy estimation and demonstrates the construction of fuzzy estimators for various important and special cases of variance, mean and distribution functions. It is shown how to use fuzzy estimators in hypothesis testing and regression, which leads to a comprehensive presentation of fuzzy hypothesis testing and fuzzy regression as well as fuzzy prediction.
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Est. Packaging Dimensions: Length: 0.5" Width: 6" Height: 9.25" Weight: 0.85 lbs.
Release Date May 27, 2004
ISBN 3540210849 ISBN13 9783540210849
Availability 0 units.
More About James J. Buckley
James J. Buckley is Professor of Theology at Loyola College in Maryland. He is the author of "Seeking the Humanity of God. "Professors Jones and Buckley are the editors of "Modern Theology" and the General Editors of the series "Blackwell Readings in Modern Theology."
L. Gregory Jones is Professor at Duke University Divinity School. He is the author of three books, including most recently "Embodying Forgiveness."
Reviews - What do customers think about Fuzzy Statistics?
fast easy reference Jan 10, 2006
The book is more like a reference book for a certain method you need for something. The whole book is actually rather short with short chapters discussing different topics. Each chapter is about 6 to 7 pages long.
The book starts with description of fuzzy sets and operations. The introduction is quick and you can go through it very fast to familiarize yourself with the notation. But I don't think you should learn fuzzy mathematics right from this book. I think having a knowledge of fuzzy logic and fuzzy sets is presumed in this book. Then each chapter is about a statistical topic like how to find mean value, standard deviation, test if mean1=mean2, etc. The chapters start discussing with method and then one example to show how it works. For that reason the redundancy in each chapter is kept to minimum and learning a topic from the book is very quick. You actually don't have to read the whole book or a big chunk of it to understand how to test mean1=mean2, but rather you just read that particular chapter and thats it. That's why I say this book is very much like reference.
Other than statistical tests, the book doesn't cover anything else, so don't use this book as an advanced course in fuzzy math.