Multidimensional Scaling and Cluste Analysis - Summary

Multidimensional Scaling and Cluste Analysis - Summary

Multidimensional scaling involves identifying dimensions by which objects are perceived and evaluated and positioning those objects and ideal objects with respect to those dimensions. The use of attribute data provides useful diagnostic information; however, it can be difficult to create a relevant and complete attribute list. The alternative is to base the perceptual map on similarity or preference data.
Cluster analysis provides a direct approach to grouping variables, objects, or people. The clusters are based on some kind of between-object similarity measure. Either hierarchical or nonhierarchical methods may be used to form clusters of objects on the basis of their between-object similarity.

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