Examine the final groupings to see whether the clusters in the final partition make intuitive sense, based on the initial partition you specified. Check that the number of observations in each cluster satisfies your grouping objectives. If one cluster contains too few or too many observations, you may want to re-run the analysis using another initial partition.
To see which cluster each observation belongs to, you must enter a storage column when you perform the analysis. Minitab stores the cluster membership for each observation in a column in the worksheet.
Step 2: Assess the variability within each cluster
Examine the variability of the observations within each cluster, using the distance from centroid measures. Clusters with higher values exhibit greater variability of the observations within the cluster. If the difference in variability between clusters is too high, you may want to re-run the analysis using another initial partition.