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Cluster analysis intends to provide groupings of set of items, objects, or behaviors that are similar to each other. The outcome of a cluster analysis provides the set of associations that exist among and between various groupings that are provided by the analysis. The actual technique depends on the application of multivariate statistics and the generation of association from available inputs. The choice of input variables becomes important in both providing the basis for similarity within a grouping and differentiating the differences between groupings.

For communication, suppose a research goal is to cluster public speakers on the basis of various behaviors exhibited during a presentation. So, a variety of behaviors are rated (e.g., speaking rate in words per minute, number of hand gestures, number of steps ...

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