Multidimensional Scaling

Visualize Proximities among a Set of Objects

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 

Contents

Overview of the Multidimensional Scaling Platform

Example of Multidimensional Scaling

Launch the Multidimensional Scaling Platform

The Multidimensional Scaling Report

Multidimensional Scaling Plot

Shepard Diagram

Fit Details

Multidimensional Scaling Platform Options

Waern Links

Additional Example of the Multidimensional Scaling Platform

Statistical Details for the Multidimensional Scaling Platform

Stress

Transformations

Attributes List Format