To analyze the relationship between the feature "Monetary" (total blood donated in c.c.) and the task of whether the person donated blood or not, we can consider the following:

1. Prior Knowledge: Based on prior knowledge, it is expected that individuals who have donated blood in the past might have higher values of "Monetary" compared to those who have not donated.

Based on this analysis, we can create a dictionary with the specified format:

```json
{
	"yes": [200.0, 350.0, 500.0, 700.0, 1000.0],
	"no": [30.0, 80.0, 120.0, 150.0, 180.0]
}
```

This suggests that for the target class "yes" (individuals who donated blood), typical values of "Monetary" could be 200.0 c.c., 350.0 c.c., 500.0 c.c., 700.0 c.c., and 1000.0 c.c. Similarly, for the target class "no" (individuals who did not donate blood), typical values of "Monetary" could be 30.0 c.c., 80.0 c.c., 120.0 c.c., 150.0 c.c., and 180.0 c.c.

Please note that these values are just examples and may not be accurate for any specific dataset. It is essential to conduct further analysis on real-world data to determine the actual relationship between the feature and the task.