To analyze the relationship between the feature "Cholesterol" and the task of determining if the coronary angiography shows heart disease, we need to determine the typical ranges of values for each target class ('no' and 'yes').

Based on prior knowledge, I will assume the following ranges for the feature "Cholesterol":

- Low cholesterol: less than 160 mm/dl
- Desirable/Normal cholesterol: 160 - 199 mm/dl
- Borderline high cholesterol: 200 - 239 mm/dl
- High cholesterol: 240 - 329 mm/dl
- Very high cholesterol: 330 mm/dl or higher

Now let's create the dictionary with the Cholesterol ranges for each target class:

```json
{
	"no": [120.5, 155.3, 187.9, 174.6, 198.2],
	"yes": [230.8, 265.4, 255.7, 275.1, 240.9]
}
```

In this example, I have randomly chosen 5 Cholesterol values for each target class to demonstrate the structure of the dictionary. However, in a real analysis, these values would be obtained from a dataset or domain-specific knowledge.