Based on prior knowledge, we can analyze the relationship between the feature "pdays" and the target variable "Does this client subscribe to a term deposit?".

The feature "pdays" represents the number of days that passed by after the client was last contacted from a previous campaign. In this analysis, we can assume that lower values of "pdays" indicate that the client was recently contacted, while higher values indicate a longer duration since the last contact.

To analyze the relationship, we can compare the average "pdays" values for clients who subscribed to a term deposit (target class "yes") and those who did not (target class "no"). Additionally, we can identify typical "pdays" values for each target class.

Here is the analysis and the resulting dictionary:

```json
{
	"no": [999.0, 998.0, 997.0, 996.0, 995.0],
	"yes": [7.0, 8.0, 10.0, 15.0, 20.0]
}
```

Based on the analysis, the typical "pdays" values for clients who did not subscribe to a term deposit (target class "no") range from 995.0 to 999.0. On the other hand, the typical "pdays" values for clients who subscribed to a term deposit (target class "yes") range from 7.0 to 20.0.

Please note that these values are just examples and may vary depending on the specific dataset being analyzed.