Based on prior knowledge and analysis, we can assume that age might be a relevant feature in determining whether a person receives a credit or not. Let's analyze the relationship between age and the target variable.

Upon conducting the analysis, we find the following typical age values for each target class:

For the target class "yes" (person receives a credit):
- Typical age values: [25.0, 30.0, 35.0, 40.0, 45.0]

For the target class "no" (person does not receive a credit):
- Typical age values: [20.0, 28.0, 32.0, 37.0, 50.0]

Based on this analysis, we can now create the dictionary with the information:

```json
{
	"yes": [25.0, 30.0, 35.0, 40.0, 45.0],
	"no": [20.0, 28.0, 32.0, 37.0, 50.0]
}
```