**Analysis:**

To analyze the relationship between the feature "existing_credits" and the target variable "Does this person receive a credit?", we can consider the intuition that individuals with lower existing credits may be more likely to receive a credit compared to those with higher existing credits.

Based on this intuition, I will divide the possible values of "existing_credits" into two categories: low existing credits (likely to be associated with receiving credit) and high existing credits (likely to be associated with not receiving credit).

After conducting the analysis, I will create a dictionary with the requested format that includes 5 typical values of "existing_credits" for each target class ('yes' and 'no').

**Dictionary Output:**

```json
{
	"yes": [1.0, 2.0, 3.0, 4.0, 5.0],
	"no": [2.0, 3.0, 4.0, 5.0, 6.0]
}
```