A. Using the data given, apply hierarchical clustering with 10 clusters using LandValue ($), BuildingValue ($), Acres,
Age, and Price ($) as variables. Be sure to Normalize input data in Step 2 of the XLMiner Hierarchical Clustering procedure, and specify complete linkage as the clustering method. Analyze the resulting clusters by computing the cluster size. It may be helpful to use a PivotTable on the data in the HC_Clusters worksheet generated by XLMiner.
You can also visualize the clusters by creating a scatter plot with Acre as the x-variable and Price ($) as the y-variable.
b. Repeat part a using average group linkage as the clustering method. Compare the clusters to the previous method.
a. Complete linkage results in clusters with extreme sizes. There are two single-home
clusters (home-45 and home-105). There is one 43-home cluster, cluster 3, which has
the average price centered at $124,927.
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In a two-card kanban system:
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