Based on prior knowledge, the credit history of a person can provide valuable information in determining whether they receive a credit or not. Here is the analysis of the relationship between the "credit_history" feature and the target variable "Does this person receive a credit?".

- 'critical/other existing credit': This category indicates that the person has critical or other existing credit. It is possible that individuals with this credit history may have a higher chance of not receiving a credit.

- 'existing paid': This category implies that the person has an existing credit history and has paid it off. Individuals with this credit history are more likely to receive a credit.

- 'delayed previously': This category suggests that the person has a history of delayed payments. It is probable that individuals with this credit history may have a lower chance of receiving a credit.

- 'no credits/all paid': This category implies that the person has no existing credits or has paid them all off. Individuals with this credit history are more likely to receive a credit.

- 'all paid': This category indicates that the person has paid all their previous credits. Individuals with this credit history are more likely to receive a credit.

Based on this analysis, the dictionary would be:

```json
{
	"yes": ["existing paid", "no credits/all paid", "all paid"],
	"no": ["critical/other existing credit", "delayed previously"]
}
```
Note that this dictionary only includes the categories that are likely to have a clear impact on the target variable. Other categories that are hard to predict or have limited impact are not included in the dictionary.