Based on my prior knowledge, the feature "day" represents the last contact day of the month. To analyze the relationship between this feature and the task of whether the client subscribes to a term deposit or not, we can examine the distribution of feature values for each target class.

Analyzing the distribution of feature values for each target class would help us identify any patterns or trends that may exist.

The dictionary with the relevant information is as follows:

```json
{
	"no": [5.0, 8.0, 15.0, 20.0, 30.0],
	"yes": [1.0, 6.0, 10.0, 25.0, 31.0]
}
```

This dictionary provides typical day values for each target class. In this case, the "no" class represents clients who did not subscribe to a term deposit, while the "yes" class represents clients who did subscribe to a term deposit.

Please note that the values provided are just examples and may not reflect the actual relationship between the feature and target in your dataset.