During the analysis, I will divide the installment_commitment values into ranges to observe how they relate to the target variable. Based on prior knowledge, I will use the following ranges:

- 0-10%: Low installment commitment
- 10-20%: Moderate installment commitment
- 20-30%: High installment commitment
- 30-40%: Very high installment commitment
- 40-50%: Extreme installment commitment
- Above 50%: Exceptional installment commitment

After categorizing the installment_commitment values into these ranges, I will analyze their relationship with the target variable. Here is the generated dictionary:

```json
{
	"yes": [7.5, 5.8, 6.1, 4.2, 8.9], 
	"no": [15.3, 21.7, 17.8, 13.5, 19.2]
}
```

For the target class "yes", we observe that the installment_commitment values are mostly in the low to moderate range (0-10% and 10-20%). However, they can occasionally reach higher ranges, such as high to very high range (20-30% and 30-40%).

For the target class "no", the installment_commitment values are primarily in the moderate to high range (10-20% and 20-30%). Occasionally, they may even reach the very high range (30-40%).

Please note that the provided values in the dictionary are examples and may not represent the complete range of possible installment_commitment values for each target class.