Based on prior knowledge, the feature "residence_since" refers to the number of years a person has been living at their current residence. To analyze its relationship with the task of credit approval, we can make some assumptions:

1. Generally, a longer duration of residence indicates stability and possibly stronger ties to the community, which can positively influence credit approval.

2. However, an extremely long duration of residence may indicate a lack of mobility and potential financial constraints, which could negatively impact credit approval.

3. Individuals who have recently moved may face uncertainties related to their financial stability and creditworthiness, potentially leading to a higher risk of credit denial.

To generate the desired dictionary, we need to identify typical residence_since values for each target class ('yes' and 'no'). Let's assume the following values:

For target class 'yes':
- 5.0
- 7.0
- 10.0
- 12.0
- 15.0

For target class 'no':
- 1.0
- 2.0
- 3.0
- 6.0
- 8.0

Here is the requested dictionary:

```json
{
	"yes": [5.0, 7.0, 10.0, 12.0, 15.0],
	"no": [1.0, 2.0, 3.0, 6.0, 8.0]
}
```