Based on prior knowledge, we can analyze the relationship between the feature "Monetary" (total blood donated in c.c.) and the task of determining whether the person donated blood or not.

Typically, individuals who donate blood are more likely to have higher values of the "Monetary" feature. On the other hand, those who did not donate blood may have lower or zero values for this feature.

Here is an analysis of the feature "Monetary" in relation to the target variable:

- For the "yes" class (person donated blood):
  - Possible values of the "Monetary" feature could be [200, 350, 500, 750, 1000] (assuming these represent c.c. of blood donated).

- For the "no" class (person did not donate blood):
  - Possible values of the "Monetary" feature could be [0, 50, 100, 150, 300] (assuming these represent c.c. of blood donated).

Based on this analysis, we can create the dictionary:

```json
{
	"yes": [200.0, 350.0, 500.0, 750.0, 1000.0],
	"no": [0.0, 50.0, 100.0, 150.0, 300.0]
}
```

Please note that the values mentioned above are for illustrative purposes and may vary in real-world scenarios.