Statistics Toolbox

Cluster Analysis

Cluster analysis, also called segmentation analysis or taxonomy analysis, is a way to partition a set of objects into groups, or clusters, in such a way that the profiles of objects in the same cluster are very similar and the profiles of objects in different clusters are quite distinct.

Cluster analysis can be performed on many different types of data sets. For example, a data set might contain a number of observations of subjects in a study where each observation contains a set of variables.

Many different fields of study, such as engineering, zoology, medicine, linguistics, anthropology, psychology, and marketing, have contributed to the development of clustering techniques and the application of such techniques. For example, cluster analysis can be used to find two similar groups for the experiment and control groups in a study. In this way, if statistical differences are found in the groups, they can be attributed to the experiment and not to any initial difference between the groups.

The following sections explore the clustering features in the Statistics Toolbox:

• Terminology and Basic Procedure
• Finding the Similarities Between Objects
• Defining the Links Between Objects
• Evaluating Cluster Formation
• Creating Clusters

The Bootstrap

Terminology and Basic Procedure