Based on my prior knowledge, there is a known relationship between serum cholesterol levels and heart disease. High levels of serum cholesterol are often associated with an increased risk of heart disease. Therefore, I would expect that patients with higher cholesterol levels might show a heart disease.

To analyze the relationship between serum cholesterol and heart disease, I would need access to a dataset that includes both the cholesterol levels and the coronary angiography results for different patients. With this information, I could divide the dataset into two groups based on the coronary angiography results (heart disease - yes or no). Then, I can examine the cholesterol levels in each group to understand the distribution and identify typical values for each target class.

Unfortunately, without access to the data, I can't perform the analysis or provide exact values for typical cholesterol levels associated with each target class. However, if I were to assume some typical values based on general knowledge, the dictionary would look as follows:

```json
{
	"no": [120.0, 150.0, 170.0, 180.0, 200.0],
	"yes": [200.0, 220.0, 240.0, 260.0, 280.0]
}
```

Please note that these values are just hypothetical examples and may not reflect the actual relationship between cholesterol levels and heart disease. It is crucial to analyze the data with real values to obtain accurate conclusions.