The agglomeration schedule is a numerical summary of the cluster solution. At the first
stage, cases 8 and 11 are combined because they have the smallest distance. The
cluster created by their joining next appears in stage 7. In stage 7, the clusters created in
stages 1 and 3 are joined. The resulting cluster next appears in stage 8. When there are
many cases, this table becomes rather long, but it may be easier to scan the coefficients
column for large gaps rather than scan the dendrogram. A good cluster solution sees a
sudden jump (gap) in the distance coefficient. The solution before the gap indicates the
good solution. The largest gaps in the coefficients column occur between stages 5 and 6,
indicating a 6-cluster solution, and stages 9 and 10, indicating a 2-cluster solution. These
are the same as your findings from the dendrogram. This is somewhat unsatisfactory as a
solution, because there isn't a strong classification. Try a solution using complete linkage
(Furthest neighbor) as the cluster method.
The agglomeration schedule is a numerical summary of the cluster solution. At the firststage, cases 8 and 11 are combined because they have the smallest distance. Thecluster created by their joining next appears in stage 7. In stage 7, the clusters created instages 1 and 3 are joined. The resulting cluster next appears in stage 8. When there aremany cases, this table becomes rather long, but it may be easier to scan the coefficientscolumn for large gaps rather than scan the dendrogram. A good cluster solution sees asudden jump (gap) in the distance coefficient. The solution before the gap indicates thegood solution. The largest gaps in the coefficients column occur between stages 5 and 6,indicating a 6-cluster solution, and stages 9 and 10, indicating a 2-cluster solution. Theseare the same as your findings from the dendrogram. This is somewhat unsatisfactory as asolution, because there isn't a strong classification. Try a solution using complete linkage(Furthest neighbor) as the cluster method.
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