Based on prior knowledge, the feature "Frequency" represents the total number of blood donations. To analyze the relationship between the frequency of donations and whether the person donated blood or not, we can make some assumptions:

1. It is reasonable to assume that individuals who donate blood more frequently are more likely to continue donating in the future, hence their frequency values may be higher.
2. Individuals who have not donated blood before (frequency = 0) might be less likely to donate blood in the future compared to those who have donated at least once.

Based on these assumptions, we can analyze the relationship between the "Frequency" feature and the target variable "Did the person donate blood?"

Dictionary:

```json
{
	"yes": [6.0, 12.0, 15.0, 18.0, 22.0],
	"no": [0.0, 1.0, 2.0, 3.0, 4.0]
}
```

In this dictionary, I have included 5 typical values for the "Frequency" feature for each target class. For the "yes" class, these values are [6.0, 12.0, 15.0, 18.0, 22.0], and for the "no" class, these values are [0.0, 1.0, 2.0, 3.0, 4.0]. These values represent a range of frequencies that individuals in each class may have.