Based on the feature description, it seems like SEQN is a respondent sequence number. To determine the appropriate ranges of values for this feature, we can use our prior knowledge about typical respondent sequences. 

Without any additional information, it is hard to determine the exact age ranges for "Adult" and "Senior" groups. However, we can make a general assumption that the "Senior" group may consist of SEQN values that are higher than the values in the "Adult" group. 

Based on this analysis, I will create a dictionary as follows:

```json
{
	"Adult": [10001.0, 10002.0, 10005.0, 10008.0, 10009.0],
	"Senior": [20001.0, 20003.0, 20005.0, 20011.0, 20012.0]
}
```

Please note that these SEQN values are just examples and may not reflect the actual dataset. Adjustments may be necessary based on the specific dataset being analyzed.