Multidimensional Scaling (MDS) is a technique that is used to create a visual representation of the pattern of proximities (similarities, dissimilarities, or distances) among a set of objects. For example, given a matrix of distances between cities, MDS can be used to generate a map of the cities in two dimensions.
Multidimensional Scaling is frequently used in consumer research where researchers have measures of perceptions about brands, tastes, or other product attributes. MDS is applicable to many other areas where one is interested in visualizing the proximity of objects based on a set of attributes or proximities.
Figure 10.1 Multidimensional Scaling Example