1. Use hierarchical clustering on the Public Utilities data set. Be sure to use the company name as a label. Use all six methods (for example, Average, Centroid, Ward, Single, Complete, and Fast Ward), and run each with the data standardized. How many clusters does each algorithm produce?

2. Repeat exercise 1, this time with the data not standardized. How does this affect the results?

3. Use hierarchical clustering on the Freshmen1.jmp data set. How many clusters are there? Use this number to perform a k-means clustering, (Be sure to try several choices of k near the one that is indicated by hierarchical clustering.) Note that k-means will not permit ordinal data. Based on the means of the clusters for the final choice of k, try to name each of the clusters.

4. Use k-means clustering on the churn data set. Try to name the clusters