In order to analyze the relationship between the feature "Time" and the target variable "Did the person donate blood?", we need to consider our prior knowledge and make some assumptions about the behavior of individuals regarding blood donation.

Based on common blood donation practices, we can assume that individuals who have donated blood more recently are more likely to donate blood again in the future. Conversely, individuals who have not donated blood for a long time are less likely to donate in the future.

Here is a dictionary that presents the relationship between the feature "Time" and the target variable:

```json
{
	"yes": [1.0, 2.0, 3.5, 4.0, 5.5],	
	"no": [17.0, 20.0, 26.0, 30.0, 40.0]
}
```

In this dictionary:
- For the target class "yes" (which represents individuals who did donate blood), the list of float values represents typical values for the feature "Time". These values indicate the number of months since the individual's first donation. The values 1.0, 2.0, 3.5, 4.0, and 5.5 are provided as examples.
- For the target class "no" (which represents individuals who did not donate blood), the list of float values represents typical values for the feature "Time". These values also indicate the number of months since the individual's first donation. The values 17.0, 20.0, 26.0, 30.0, and 40.0 are provided as examples.

Please note that the values presented in the dictionary are just examples and may not reflect the actual distribution of the feature "Time" for each target class.