Fuzzy set theory deals with sets or categories whose boundaries are blurry or, in other words, "fuzzy." This book presents an accessible introduction to fuzzy set theory, focusing on its applicability to the social sciences. Unlike most books on this topic, Fuzzy Set Theory: Applications in the Social Sciences provides a systematic, yet practical guide for researchers wishing to combine fuzzy set theory with standard statistical techniques and model-testing.

Key Features:

• Addresses Basic Concepts: Fuzzy set theory is an analytic framework for handling concepts that are simultaneously categorical and dimensional. Starting with a rationale for fuzzy sets, this book introduces readers with an elementary knowledge of statistics to the necessary concepts and techniques of fuzzy set theory and fuzzy logic.
• Introduces Novel Ways of Analyses: Researchers are shown alternative methods to conventional models, especially for testing theories that are expressed in set-wise terms. Issues of operationalizing graded membership in a fuzzy set and the measurement of the properties of such sets are a few of the topics addressed.
• Illustrates Techniques and Applications: Real examples and data-sets from various disciplines in the social sciences are used to demonstrate the connections between fuzzy sets and other data analytic techniques, empirical applications of the technique, and the critiques of fuzzy set theory.

Intended Audience:
Ideal for researchers in the social sciences, education, and behavioral sciences; as well as graduate students in the applied social sciences



About the Author
Michael Smithson is a Professor in the Research School of Psychology at The Australian National University in Canberra, and received his PhD from the University of Oregon. He is the author of Confidence Intervals (2003), Statistics with Confidence (2000), Ignorance and Uncertainty (1989), and Fuzzy Set Analysis for the Behavioral and Social Sciences (1987), co-author of Fuzzy Set Theory: Applications in the Social Sciences (2006) and Generalized Linear Models for Categorical and Limited Dependent Variables (2014), and co-editor of Uncertainty and Risk: Multidisciplinary Perspectives (2008) and Resolving Social Dilemmas: Dynamic, Structural, and Intergroup Aspects (1999). His other publications include more than 170 refereed journal articles and book chapters. His primary research interests are in judgment and decision making under ignorance and uncertainty, statistical methods for the social sciences, and applications of fuzzy set theory to the social sciences. Jay Verkuilen, PhD, is an associate professor of educational psychology at the City University of New York Graduate Center. His methodological research work is primarily in the area of psychometrics and statistics. His empirical work focuses on measurement in education and clinical psychology, and statistical analysis of rehabilitation medicine, particularly in the area of aphasia. He is the author of several publications regarding fuzzy set theory in behavioral science.

Reviews
"I think that the book is a simple and accessible introduction to the theory of fuzzy sets and it includes many examples, formulae, figures, and tables which illustrate its contents. The presentation of the book and the academic content are very careful, which make for pleasant reading." -- Marinano Ruiz Espejo



Book Information
ISBN 9780761929864
Author Michael Smithson
Format Paperback
Page Count 112
Imprint SAGE Publications Inc
Publisher SAGE Publications Inc
Weight(grams) 140g