Based on prior knowledge and assuming that the feature "day" represents the last contact day of the month, we can analyze its relationship with the target variable "Does this client subscribe to a term deposit?".

To do so, we can compare the distribution of feature values for each target class ('no' and 'yes'). By examining these distributions, we can identify typical values for each target class.

Once we have analyzed the relationship, we can create the requested dictionary with the respective day values for each target class.

Here is the dictionary with the typical day values for each target class:

```json
{
	"no": [5.0, 15.0, 20.0, 25.0, 30.0], 
	"yes": [1.0, 10.0, 15.0, 20.0, 31.0]
}
```

Note: The specific values provided in the dictionary are just examples based on a hypothetical analysis. The actual values may vary depending on the dataset and analysis performed.