Run the Cluster Analysis in JMP using k-means method. Include all the variables. Choose 4 clusters and save script to your data table. ALSO Save the clusters in the data using "Save Clusters" It should look like the below: Cluster Means Amount Last Spent Purchase Total First Related Children's Cluster Gender Purchase Purchase Purchase Books 1 0.73228346 281.768504 14.7748031 8.91338583 50.6425197 0.84566929 1.77480315 2 0.69590643 277.163743 15.6842105 7.86549708 46.7836257 3.0994152 1.48538012 3 0.67741935 284.799007 14.2084367 7.37717122 43.2183623 3.05707196 1.17617866 4 0.70261555 176.020781 12.8169115 1.91866714 17.3600026 0.4446435 0.25223934 Youth Books Cook Books 0.0015748 2.05826772 0.66081871 1.65497076 0.71712159 1.42183623 0.11035471 0.27302042 Reference Geography Italian Italian Art History Craft Books Books Art Books Books Cook Books Italian Atlas Art Books Florence 1.06456693 0.72283465 0.18267717 0.40314961 0.13070866 0.12913386 0 0.11811024 0.8245614 0.58479532 0.68421053 0.71345029 0.43859649 0.20467836 1.06432749 0.38011696 0.60297767 0.52109181 0.96526055 1.71960298 0.31265509 0.06451613 0 0.31761787 0.12289502 0.0917234 0.19132927 0.17233966 0.07774991 0.00250006 0.00071659 0.10856324 List the distinctive qualities (using information from the Cluster Means table) of each cluster and give them a name that helps identify them