To analyze the relationship between the feature DIQ010 and the task of predicting a person's age group (senior or non-senior), we will consider the prior knowledge and determine the appropriate ranges of values for diabetes status.

Based on prior knowledge, we can assume that DIQ010 has the following values:
- 1: Yes, has been told had diabetes (adult-onset)
- 2: Yes, has been told had diabetes (childhood-onset)
- 3: Yes, has been told has prediabetes (adult-onset)
- 4: Yes, has been told has prediabetes (childhood-onset)
- 5: No, told not at risk
- 6: No, risk unknown
- 7: Refused
- 9: Don't know

We will assign the following age groups:
- Adult: If the respondent is 18 years or older
- Senior: If the respondent is 65 years or older

Let's analyze the relationship between DIQ010 and the age group to create the requested dictionary:

```json
{
	"Adult": [1.0, 3.0, 5.0, 6.0, 7.0],
	"Senior": [1.0, 3.0, 5.0, 6.0, 9.0]
}
```

In the above dictionary, we have listed 5 typical DIQ010 values for each target class ('Adult' and 'Senior'). The values are represented as floats in lists.