Based on prior knowledge and assuming that a larger number of dependents might indicate more financial responsibilities, we can analyze the relationship between the num_dependents feature and the task of determining whether a person receives credit or not. Here is the dictionary containing the information:

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

In the case of 'yes', we have chosen typical values of num_dependents to be 0, 1, 2, 3, and 4. These values indicate the number of dependents a person may have when they are still eligible for receiving credit.

Similarly, for the 'no' case, we have selected typical values of 0, 1, 2, 3, and 4 for num_dependents. These values indicate the number of dependents a person may have when they are not eligible for receiving credit.

Please note that these specific values are just examples and may vary depending on the dataset and the context of the problem.