Based on prior knowledge, we can assume that age might be an important factor in determining whether a person receives a credit or not. Typically, younger individuals might have more difficulty obtaining credit due to limited credit history, while older individuals might have a higher likelihood of receiving credit.

Here is the dictionary with typical age values for each target class:

```json
{
	"yes": [25.0, 28.0, 30.0, 32.0, 35.0],
	"no": [40.0, 45.0, 50.0, 55.0, 60.0]
}
```

These values are just examples and may vary depending on the specific dataset.