Based on my prior knowledge and understanding of the feature description, I will analyze the relationship between the feature "day" and the task of whether the client subscribes to a term deposit or not.

Analyzing the relationship between the feature "day" and the target class:

- Typically, bank marketing campaigns are carried out monthly, so the "day" feature represents the last contact day of the month.
- It is possible that the specific day of the month on which a client is contacted may have some influence on their decision to subscribe to a term deposit or not.
- However, it is important to note that without more context or additional information, it is difficult to determine exact patterns or predict the relationship solely based on the feature "day" itself.

Based on this analysis, let's create a dictionary with typical day values for each target class:

```json
{
	"no": [5.0, 10.0, 15.0, 20.0, 25.0],
	"yes": [2.0, 8.0, 13.0, 18.0, 28.0]
}
```

Note: These values are just examples and may not reflect the actual patterns in the dataset. Further analysis and statistical tests would be required to determine the true relationship between the "day" feature and the target variable.