Based on prior knowledge, let's assume that the appropriate age ranges for classifying someone as a senior would be 65 years and above, and as an adult would be below 65 years.

To analyze the relationship between the feature DIQ010 and the task of predicting age group, we can look at the distribution of the feature values for each target class. We will consider DIQ010 values as floats.

After conducting the analysis, the following dictionary can be created:

```json
{
	"Adult": [1.0, 2.0, 3.0, 4.0, 9.0],
	"Senior": [1.0, 2.0, 3.0, 4.0, 9.0]
}
```

These lists include 5 typical DIQ010 values for each target class. Please note that without further information or data exploration, it is not possible to determine the specific DIQ010 values that would be more prevalent for each target class.