Based on my prior knowledge, the feature "other_payment_plans" represents the presence of other installment plans (banks, stores) for the person. To analyze its relationship with the task of whether the person receives a credit or not, I would compare the distribution of "other_payment_plans" for each class of the target variable.

Here is the analysis and the resulting dictionary:

```json
{
	"yes": ["none", "bank", "stores"],
	"no": ["none", "bank", "stores"]
}
```

Explanation:
- For the target class "yes" (person receives a credit), all three possible values of "other_payment_plans" are present. This suggests that people who receive credit may have various other installment plans, including no plan, bank plans, or plans with stores.
- For the target class "no" (person does not receive a credit), the same three possible values of "other_payment_plans" are also present. This indicates that even if a person does not receive credit, they can still have other installment plans, such as bank plans or plans with stores.

Therefore, both target classes have the same possible values for the "other_payment_plans" feature, implying that this feature is not strongly indicative of whether a person receives a credit or not.