Based on prior knowledge and assumption that longer duration of last contact might have a positive impact on the probability of the client subscribing to a term deposit, we can analyze the relationship between the feature "duration" and the target variable "does the client subscribe to a term deposit?".

Here is the analysis and the generated dictionary:

```json
{
    "no": [30.0, 60.0, 90.0, 120.0, 150.0],
    "yes": [240.0, 270.0, 300.0, 330.0, 360.0]
}
```

In the above dictionary, the key "no" represents the target class "no" and the list of values [30.0, 60.0, 90.0, 120.0, 150.0] are some examples of typical duration values for this class. Similarly, the key "yes" represents the target class "yes" and the list of values [240.0, 270.0, 300.0, 330.0, 360.0] are some examples of typical duration values for this class.

Please note that the range and actual values of duration may vary based on the specific dataset and context. The values provided here are just examples for illustrative purposes.