Cluster analysis is a technique that groups similar data points into clusters based on some criteria, such as distance, density, or similarity. It can be useful for finding patterns, insights, or ...

Ultimately, internal validity measures are only one aspect of cluster analysis robustness, and they should be used with caution and interpretation. Add your perspective Help others by sharing more ...

Example 42.3: Cluster Analysis with Significance Tests This example uses artificial data containing two clusters. One cluster is from a circular bivariate normal distribution. The other is a ...

Cluster analysis is a technique used to group sets of objects that share similar characteristics. It is common in statistics. Investors will use cluster analysis to develop a cluster trading ...

Example 59.1: Standardization of Variables in Cluster Analysis To illustrate the effect of standardization in cluster analysis, this example uses the Fish data set described in the "Getting Started" ...

The DuPont analysis is a formula used to evaluate a company's financial performance based on its return on equity (ROE). By most accounts, it was devised in 1919 by a DuPont executive.

Conclusions Cluster analysis of isometric strength tests produced classes comprising athletes who experienced a similar degree of activity limitation. The strength tests reported can provide the basis ...

In a cluster randomised clinical trial, all the participants who belong to the same cluster (eg, a local community, school, or general practice) are randomised to receive the same treatment. People ...