Encyclopedia of Statistics in Behavioral Science Everitt Behavioral
Cluster Analysis: Overview
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Manton, KG; Lowrimore, G; Yashin, A; Kovtun, M
January 1, 2006
This article discusses analysis techniques for clustering objects into hopefully meaningful sets. Hierarchical methods are presented for clustering both variables and cases. Examples are presented for variations on the methods. A nonhierarchical method, k-means, is discussed for continuous data. Finally, an example comparing the results of k-means clustering to an ad hoc method using principal components analysis is given.
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Manton, K. G., Lowrimore, G., Yashin, A., & Kovtun, M. (2006). Cluster Analysis: Overview. In Encyclopedia of Statistics in Behavioral Science Everitt Behavioral (pp. 1–10). https://doi.org/10.1002/0470013192.bsa101
Manton, K. G., G. Lowrimore, A. Yashin, and M. Kovtun. “Cluster Analysis: Overview.” In Encyclopedia of Statistics in Behavioral Science Everitt Behavioral, 1–10, 2006. https://doi.org/10.1002/0470013192.bsa101.
Manton KG, Lowrimore G, Yashin A, Kovtun M. Cluster Analysis: Overview. In: Encyclopedia of Statistics in Behavioral Science Everitt Behavioral. 2006. p. 1–10.
Manton, K. G., et al. “Cluster Analysis: Overview.” Encyclopedia of Statistics in Behavioral Science Everitt Behavioral, 2006, pp. 1–10. Scopus, doi:10.1002/0470013192.bsa101.
Manton KG, Lowrimore G, Yashin A, Kovtun M. Cluster Analysis: Overview. Encyclopedia of Statistics in Behavioral Science Everitt Behavioral. 2006. p. 1–10.