Based on prior knowledge, we can analyze the relationship between the feature "num_dependents" and the task of determining whether a person receives credit or not. Here is the analysis:

- In general, individuals with a higher number of dependents may be less likely to receive credit, as they may have higher financial responsibilities and potentially less disposable income to repay the credit.
- However, the relationship may not be linear, and there might be specific ranges or thresholds where the likelihood of receiving credit changes significantly.

Based on this analysis, I will now create a dictionary with typical num_dependents values for each target class:

```json
{
	"yes": [1.0, 0.0, 2.0, 3.0, 0.5],
	"no": [0.0, 1.5, 4.0, 1.0, 2.5]
}
```

Please note that these values are just representative examples and not exhaustive. The actual values of num_dependents can vary based on the specific dataset and context.