Hierarchical Cluster Analysis Measures for Interval Data

The following dissimilarity measures are available for interval data:

• Euclidean distance. The square root of the sum of the squared differences between values for the items. This is the default for interval data.
• Squared Euclidean distance. The sum of the squared differences between the values for the items.
• Pearson correlation. The product-moment correlation between two vectors of values.
• Cosine. The cosine of the angle between two vectors of values.
• Chebychev. The maximum absolute difference between the values for the items.
• Block. The sum of the absolute differences between the values of the item. Also known as Manhattan distance.
• Minkowski. The pth root of the sum of the absolute differences to the pth power between the values for the items.
• Customized. The rth root of the sum of the absolute differences to the pth power between the values for the items.