When exploring and describing large data sets, it is sometimes useful to summarize the information by assigning each subject or item to a group with similar characteristics. This process is called classification.
Cluster analysis is a family of methods for discovering natural classifications of items.
Cluster analysis was originally developed to aid biologists in classifying plants and animals, but there are many different applications in fields from marketing to medicine. For example, a researcher was interested in describing dietary attitudes. Each subject was given a list of attitudes towards food and asked whether he or she agreed with the attitudes. No criteria existed for classifying subjects on the basis of their food attitudes, and the researcher did not know in advance how many or what groups might be found. Cluster analysis was used to determine whether a natural grouping existed.