Notice
You are now leaving support.minitab.com.
Click Continue to proceed to:
A business analyst wants to classify 22 successful small-to-medium size manufacturing companies into meaningful groups for future analyses. The analyst collects data on the number of clients, rate of return, sales, and the years the companies have been in business. To start the partition process, the analyst divides the companies into three initial groups: established, mid-growth, and young.
You can use this data to demonstrate Cluster K-Means, Matrix Plot, and other analyses that use multiple related measurement variables.
| Worksheet column | Description |
|---|---|
| Company | The company identifier |
| Clients | The number of clients that the company has |
| Rate of Return | The rate of return (sales) on investment (advertising) for the past year |
| Sales | The sales for the past year |
| Years | The number of years that the company has been in business |
| Initial | For Cluster K-Means analysis: The initial best guess of cluster membership to begin the partition process, based on number of clients, rate of return, sales, and years in business: 0 = no guess, 1 = Established company, 2 = Mid-growth company, or 3 = Young company |
| Group | Cluster K-Means analysis results: The final partition of groups |
You are now leaving support.minitab.com.
Click Continue to proceed to: