Based on prior knowledge, the feature "job" is likely to have some influence on whether a client subscribes to a term deposit or not. Different types of jobs may have different levels of income, stability, and financial responsibilities, which can impact the likelihood of subscribing.

To analyze the relationship between the feature "job" and the task of subscribing to a term deposit, we can examine the distribution of job types for each target class (yes and no).

After conducting the analysis, the dictionary would look like this:

```json
{
    "no": ["blue-collar", "unknown", "services", "housemaid", "unemployed", "student"],
    "yes": ["management", "technician", "entrepreneur", "retired", "admin.", "self-employed"]
}
```

The values in the "no" list represent job types that are more likely to be associated with clients who do not subscribe to a term deposit. The values in the "yes" list represent job types that are more likely to be associated with clients who do subscribe to a term deposit.