Based on prior knowledge, we can analyze the relationship between the credit_amount feature and the task of determining whether a person receives credit.

Since no specific range is provided, we will make an assumption based on common credit practice. In general, credit amounts can vary widely depending on the purpose of the loan and the borrower's financial situation. However, we can consider the following ranges as a starting point:
1. Small Loan: $1,000 - $5,000
2. Medium Loan: $5,000 - $15,000
3. Large Loan: $15,000 - $30,000
4. Very Large Loan: $30,000 - $50,000
5. Extremely Large Loan: Above $50,000

Now, let's analyze the relationship between credit_amount and whether a person receives credit based on these ranges:

```json
{
	"yes": [
		1000.0,
		1500.0,
		3000.0,
		8000.0,
		20000.0
	],
	"no": [
		500.0,
		2000.0,
		10000.0,
		25000.0,
		60000.0
	]
}
```

In the above dictionary, we provide 5 typical credit_amount values for each target class ('yes' and 'no'). These values are just a representation and can differ based on the specific dataset.