 Cluster AnalysisThomas Cleff
Chapter 7 in Exploratory Data Analysis in Business and Economics, 2014, pp 163-182 from Springer Abstract: Abstract Before we turn to the subject of cluster analysis, think for a moment about the meaning of the word cluster. The term refers to a group of individuals or objects that converge around certain point, and are thus closely related in their position. In astronomy there are clusters of stars; in chemistry, clusters of atoms. Economic research often relies on techniques that consider groups within a total population. For instance, firms that engage in target group marketing must first divide consumers into segments, or clusters of potential customers. Indeed, in many contexts researchers and economists need accurate methods for delineating homogenous groups within a set of observations. Groups may contain individuals (such as people or their behaviours) or objects (such as firms, products, or patents). This chapter thus takes a cue from Goethe’s Faust: “You soon will [understand]; just carry on as planned/You’ll learn reductive demonstrations/And all the proper classifications.” Keywords: Hierarchical Cluster Analysis; Cluster Solution; Linkage Method; Proximity Measure; Initial Partition (search for similar items in EconPapers) There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-01517-0_7 Ordering information: This item can be ordered from DOI: 10.1007/978-3-319-01517-0_7 Access Statistics for this chapter More chapters in Springer Books from Springer |
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