Based on my prior knowledge, the feature "checking_status" can be a strong indicator of whether a person receives credit or not. Here is an analysis of the relationship between this feature and the target variable "Does this person receive a credit?".

- "<0" (less than 0) checking_status: People with a checking_status of "<0" may have a higher likelihood of not receiving credit. This could indicate a negative balance or insufficient funds in their checking account.

- "0<=X<200" (between 0 and 200) checking_status: People with a checking_status of "0<=X<200" may have a moderate likelihood of receiving credit. This range indicates a somewhat stable checking account balance.

- "no checking" checking_status: People with a checking_status of "no checking" may have a lower likelihood of receiving credit. This suggests that they do not have a checking account, which can be considered a risk factor for lenders.

- ">=200" (greater than or equal to 200) checking_status: People with a checking_status of ">=200" may have a higher likelihood of receiving credit. This indicates a stable or even substantial balance in their checking account.

Based on this analysis, here is the dictionary representing the relationship between "checking_status" and the target variable:

```json
{
	"yes": ["0<=X<200", ">=200"], 
	"no": ["<0", "no checking"]
}
```

Please note that this analysis is based on generalized observations and may not be accurate for all scenarios. Further statistical analysis and modeling techniques can provide more precise insights.