Based on prior knowledge, we can analyze the relationship between the feature "duration" and the task of whether the client subscribes to a term deposit or not.

To do this, we can look at typical duration values for each target class ('no' for not subscribing and 'yes' for subscribing). By examining these values, we can identify any patterns or differences that may exist.

Here is the dictionary analysis for the feature "duration" based on the given task:

```json
{
   "no": [58.0, 102.0, 183.0, 210.0, 245.0],
   "yes": [305.0, 320.0, 389.0, 445.0, 534.0]
}
```

In the above analysis, we have included 5 typical duration values for each target class. The "no" class has durations ranging from 58.0 seconds to 245.0 seconds, while the "yes" class has durations ranging from 305.0 seconds to 534.0 seconds.

These values suggest that there may be a relationship between the duration of the last contact and whether the client subscribes to a term deposit or not. Clients with longer durations tend to be more likely to subscribe to a term deposit. However, further data analysis and modeling would be needed to confirm and quantify this relationship.