Based on prior knowledge, we can analyze the relationship between the "residence_since" feature and the task of determining whether a person receives credit or not. 

Generally, a longer duration of residence in a particular location can indicate stability and potentially increase the probability of receiving credit. However, it is important to conduct a thorough analysis to confirm this relationship.

To create the dictionary with the requested format, we will need to examine the distribution of "residence_since" values for each target class ('yes' and 'no').

Here is the dictionary with the analysis:

```json
{
    "yes": [1.5,3.0,4.0,2.5,6.0],
    "no": [0.5,2.0,7.0,1.0,0.2]
}
```

Please note that the values provided in the dictionary are just examples and may not accurately represent the actual relationship between the "residence_since" feature and the target variable.