Provide a few sentences on the differences and which you believe had led to better clustering and why

6. The Football Bowl Subdivision (FBS] level of the National Collegiate Athletic Association (NCAA) consists of over 100 schools. Most of these school belong to one of several conferences, or collections of schools, that compete with each other on a regular basis in collegiate sports. Suppose the NCAA has commissioned a student that will propose the formation of conferences based on the similarities of the constituent schools. The file FBS contains data on schools that belong to the FBS. Each row in this file contains information on a school. The variables include football stadium capacity, latitude, longitude, athletic department revenue, endowment, and undergraduate enrollment. (A) Use k-means clustering as they want 10 clusters, using the variables capacity, latitude, longitude, revenue, endowment, and enrollment. Be sure to normalize data and set the number of clusters to 10 without limit on iterations. Provide the frequency count in each cluster. Cluster Frequency 11 2 10 3 12 2 5 32 7 32 12 10 11 (8)Repeat this process with 10 clusters, but change the standardization method to range. Provide the frequency for those clusters as you did above. Cluster | Frequency 1 9 2 33 11 3 3 23 Cluster Frequency 17 10 14 (C)Provide a few sentences on the differences and which you believe had led to better clustering and why