Proposed Analyses:
------------------
k-means clustering
correlation
PCA
dimension reduction - done
hierarchical clustering 
 -	In single-linkage clustering (also called the connectedness or minimum
	method), we consider the distance between one cluster and another cluster
	to be equal to the shortest distance from any member of one cluster to any
	member of the other cluster. If the data consist of similarities, we
	consider the similarity between one cluster and another cluster to be equal
	to the greatest similarity from any member of one cluster to any member of
	the other cluster.
 -	In complete-linkage clustering (also called the diameter or maximum
	method), we consider the distance between one cluster and another cluster
	to be equal to the greatest distance from any member of one cluster to any
	member of the other cluster.
 -	In average-linkage clustering, we consider the distance between one cluster
	and another cluster to be equal to the average distance from any member of
	one cluster to any member of the other cluster.
 - 	http://www.elet.polimi.it/upload/matteucc/Clustering/tutorial_html/hierarchical.html

Proposed Results:
-----------------
TotalResults - done
MeanResults - done
VarianceResults - done
StDevResults - done
MinResults - done
MaxResults - done
