Many clustering algorithms require globular (gaussian) clusters. Main example is k-means. If clusters are not globular, these methods can bring wrong results.
In social sciences, data is often clustered by these algorithms (market segmentation is very common example). My question then is whether there are some reasons why we should regard clusters from social surveys as globular (and therefore appropriate for methods like k-means).
An example of social data that could be clustered is mentioned in my previous question. I asked my students to rate selected interest (1-5 scale) and the task then could be to cluster students according to similar interests.