Based on prior knowledge, let's analyze the relationship between the feature "num_dependents" and the task of whether a person receives credit or not.

Analysis:
The number of dependents a person has can potentially impact their ability to receive credit. Typically, having more dependents increases the financial burden on an individual, making it more difficult for them to meet their financial obligations. Therefore, it can be expected that individuals with higher values of "num_dependents" may be less likely to receive credit.

However, it's important to note that the impact of "num_dependents" on the task of receiving credit can vary depending on the specific lending institution, policies, and individual circumstances. Therefore, it is necessary to analyze the data to understand the relationship more accurately.

Now, let's create the dictionary with the specific details:

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

In this dictionary, we include five typical values of "num_dependents" for each target class ('yes' and 'no'). These values are presented as floats in the lists. Please note that the specific values provided here are just for demonstration purposes, and the actual values may vary depending on the dataset being analyzed.