This book explains and illustrates the most frequently used methods of hierarchical cluster analysis so that they can be understood and practiced by researchers with limited backgrounds in mathematics and statistics. Widely applicable in research, these methods are used to determine clusters of similar objects. For example, ecologists use cluster analysis to determine which plots (i.e. objects) in a forest are similar with respect to vegetation growing on them; medical researchers use cluster analysis to determine which brands of products the public perceives similarly. In all fields of research, there exists this basic and recurring need to determine clusters of objects. This book will ground you in the basic methods of cluster analysis and guide you in all phases of their use. You will learn how to recognize when you have a research problem that requires cluster analysis, how to decide upon the most appropriate kind of data to collect, how to choose the best method of cluster analysis for your problem, how to obtain a computer program to perform the necessary calculations, and how to interpret the results A Road Map To This Book. -- Part. 1. Overview Of Cluster Analysis: Basics--the Six Steps Of Cluster Analysis ; General Features Of Cluster Analysis ; Applications Of Cluster Analysis In Retroductive And Hypothetico-deductive Science ; Applications Of Cluster Analysis In Making Classifications ; Applications Of Cluster Analysis In Planning And Engineering. -- Part 2. How To Do Cluster Analysis In Depth: Standardizing The Data Matrix ; Resemblance Coefficients For Quantitative Attributes ; Clustering Methods ; Resemblance Coefficients For Qualitative Attributes ; Special Resemblance Coefficients For Ordinal-scaled Attributes ; Resemblance Coefficients For Mixtures Of Quantitative And Qualitative Attributes ; Bypassing The Data Matrix ; Matrix Correlation ; How To Present The Results Of A Cluster Analysis . -- Part 3. How To Use Cluster Analysis To Make Classifications: How To Make Classifications ; How To Identify Objects Into A Classification ; Philosophy Of Classification And Identification. -- Part 4. Cluster Analysis --philosophy: The Six Steps Of Research ; The Roles Of Information, Tolerances, And Norms In Research ; Framing And Validating In Cluster Analysis ; Examples Illustrating How To Frame And Validate Applications Of Cluster Analysis ; The Orders Of Patterns Of Similarity -- Appendix 1. Books And Articles On Cluster Analysis And Other Multivariate Methods. -- Appendix 2. Computer Programs For Cluster Analysis. H. Charles Romesburg. Includes Index. Bibliography: P. 318-329.
