Based on prior knowledge, we can analyze the relationship between the "age" feature and the task of whether a client subscribes to a term deposit.

Typically, younger clients may be less likely to subscribe to a term deposit due to lower financial stability and fewer savings. On the other hand, older clients may be more interested in secure investments like term deposits.

To create the dictionary, we need to identify typical age values for each target class ('no' and 'yes').

Assuming 'no' represents clients who did not subscribe to a term deposit and 'yes' represents clients who did subscribe, here is a possible analysis:

```json
{
  "no": [25.0, 30.0, 35.0, 40.0, 45.0],
  "yes": [50.0, 55.0, 60.0, 65.0, 70.0]
}
```

This dictionary indicates that typical age values for clients who did not subscribe to a term deposit ('no') range from 25 to 45 years, with values such as 25.0, 30.0, 35.0, 40.0, and 45.0. For clients who did subscribe ('yes'), typical age values range from 50 to 70 years, with values such as 50.0, 55.0, 60.0, 65.0, and 70.0.

Please note that the provided values are just examples, and the range and actual typical age values may vary based on the specific dataset and analysis.