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Clustering is a multivariate technique that groups observations together that share similar values across a number of variables. Hierarchical clustering combines rows in a hierarchical sequence that is portrayed as a tree. Cereals with certain characteristics, such as high fiber, are grouped in clusters so that you can view similarities among cereals.
1.
With Cereal.jmp displayed, select Analyze > Clustering > Hierarchical Cluster.
2.
Select Calories through Enriched, click Y, Columns, and then click OK.
The Hierarchical Clustering report appears. Figure  .11 shows a portion of the report. The clusters are colored according to the data table row states.
Figure  .11 Portion of the Hierarchical Clustering Report
3.
Select Color Clusters from the Hierarchical Clustering red triangle menu.
Figure  .12 Colored Clusters
Figure  .13 Similar Cereals in Cluster One
Figure  .14 Selecting a Cluster
5.
To see the similar characteristics in the cluster, select Cluster Summary from the red triangle menu.
Figure  .15 Cluster Summary
Figure  .16 Cluster One Characteristics

Help created on 3/19/2020