To analyze the relationship between the feature "Insulin" and the task of determining whether a person has diabetes or not, we can use our prior knowledge to determine the appropriate ranges of insulin values.

Typically, individuals without diabetes have lower insulin levels compared to those with diabetes. However, it is important to note that insulin levels can vary depending on various factors such as age, body weight, and other individual characteristics.

Based on this knowledge, we can proceed to create the dictionary. Here's the markdown code snippet representing the relationship between the feature and the target:

```json
{
	"yes": [25.0, 45.0, 60.0, 75.0, 100.0],
	"no": [4.0, 8.0, 12.0, 18.0, 22.0]
}
```

In this dictionary, the values within the "yes" list represent typical insulin values for individuals with diabetes, while the values within the "no" list represent typical insulin values for individuals without diabetes. It's important to note that these values are just examples and may not necessarily apply universally. The actual values can vary depending on the dataset and population being analyzed.