Analyzing the relationship between the feature "num_dependents" and the target variable "Does this person receive a credit?" can be done based on prior knowledge and common sense assumptions.

Assuming that higher values of "num_dependents" may indicate more financial responsibility and potentially lower financial stability, we can hypothesize that individuals with a higher number of dependents may have a lower chance of receiving credit.

Based on this assumption and the given task, we can perform an analysis of the relationship between the "num_dependents" feature and the "Does this person receive a credit?" target variable.

Here is a dictionary with possible values of the "num_dependents" feature for each target class:

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

Note: The ranges of values for the "num_dependents" feature have not been specified explicitly, so I have assumed a range from 0 to 4 in this case. Please adjust the values accordingly if a different range is applicable.