Based on the feature description, it seems like installment_commitment represents the percentage of a person's disposable income that is committed to paying installments. To analyze the relationship between this feature and the task of receiving credit, we can assume that a higher installment_commitment would make it harder for a person to receive credit, as a larger proportion of their income is already committed to installments.

To create the dictionary as requested, we can look at typical values of installment_commitment for each target class:

```json
{
	"yes": [10.0, 15.0, 20.0, 25.0, 30.0],
	"no": [40.0, 45.0, 50.0, 55.0, 60.0]
}
```

These values are just examples and can be adjusted based on prior knowledge or data analysis. In this case, we assume that lower installment_commitment values represent a higher chance of receiving credit, so the values for 'yes' tend to be lower, while the values for 'no' tend to be higher.

Please note that the ranges and values mentioned here are illustrative and might not hold true for the actual data. It is important to analyze the data and consider prior knowledge to determine the appropriate ranges and values for a specific dataset.