Based on prior knowledge, the marital status of a client can potentially have an influence on whether they subscribe to a term deposit or not. Let's analyze the relationship between the "marital" feature and the target variable "subscribed to a term deposit" (yes or no).

To do this, we can examine the distribution of marital statuses among clients who did not subscribe to a term deposit (target class "no") and those who did subscribe (target class "yes").

Here is the dictionary with the relevant details:

```json
{
	"no": ["married", "single", "divorced"],
	"yes": ["married", "single", "divorced"]
}
```

Based on the given categories, it appears that all three marital statuses (married, single, and divorced) occur for both target classes (yes and no).