Based on prior knowledge, it is expected that individuals who donate blood regularly will have higher values in the feature "Monetary" compared to those who do not donate blood.

To generate the dictionary with specific details, I will analyze the relationship between the feature "Monetary" and the target variable "Did the person donate blood?".

To determine the appropriate ranges of values for "Monetary", let's assume the following:

- "Monetary" values range from 0 to 10,000 c.c.
- People who donated blood may have "Monetary" values of at least 500 c.c. (considered as a typical threshold for regular donors).

Based on these assumptions, we can now analyze the relationship between the feature "Monetary" and the target variable.

```json
{
	"yes": [
		1000.0,
		1500.0,
		2000.0,
		2500.0,
		3000.0
	],
	"no": [
		50.0,
		100.0,
		250.0,
		400.0,
		800.0
	]
}
```
In this example, we assume that individuals with "Monetary" values ranging from 1000 to 3000 c.c. are typical donors (class 'yes'), while those with values ranging from 50 to 800 c.c. are non-donors (class 'no').

Please note that these values are for illustrative purposes and can be adjusted based on specific domain knowledge or dataset analysis.