Based on prior knowledge, we can analyze the relationship between age and the likelihood of having diabetes. Older age is generally associated with a higher risk of developing diabetes, so there may be a positive correlation between age and the likelihood of having diabetes.

To create the requested dictionary, we need to examine the age values for each target class ('yes' and 'no'). Here is a possible analysis:

```json
{
	"yes": [40.5, 50.7, 55.3, 62.1, 67.2],
	"no": [25.2, 30.4, 35.9, 42.6, 48.3]
}
```

In this example, we included five typical age values for each target class. The values are presented as floats in the lists. Keep in mind that these values are illustrative and may not represent the actual data.