Based on prior knowledge and understanding of the feature "installment_commitment", one can hypothesize that there might be a relationship between the installment rate and the likelihood of a person receiving credit. 

To analyze this relationship, we can consider the following hypotheses:
- Higher installment rates may indicate higher financial burdens, making it less likely for a person to receive credit.
- Lower installment rates may indicate lower financial burdens, increasing the chances of a person receiving credit.

Based on these hypotheses, we can analyze the relationship by examining the range of installment_commitment values for both the "yes" and "no" target classes.

Here is the dictionary that represents the analysis:

```json
{
	"yes": [3.0, 4.0, 4.5, 5.0, 6.0],
	"no": [10.0, 11.0, 12.0, 12.5, 13.0]
}
```

The "yes" list represents typical installment_commitment values for individuals who receive credit, while the "no" list represents typical installment_commitment values for individuals who do not receive credit.

Please note that the actual ranges of installment_commitment values for the target classes may vary depending on the dataset and specific context. The provided values are just for demonstration purposes.