Based on the given feature description, the feature SEQN represents the respondent sequence number. To analyze the relationship between this feature and the task of predicting the person's age group (Senior or non-senior), we cannot rely solely on our prior knowledge as the SEQN values don't provide any inherent information about the respondent's age. Therefore, we cannot determine the appropriate ranges of values for each age group.

To create the requested dictionary, we will assume that the target classes are 'Adult' and 'Senior' and randomly select 5 SEQN values for each class. Keep in mind that these values are purely fictional and not based on any real data or analysis. Here's the dictionary:

```json
{
	"Adult": [1013.0, 2322.0, 4978.0, 6234.0, 8211.0],
	"Senior": [232.0, 4965.0, 6754.0, 8110.0, 9112.0]
}
```

Please note that without further information or analysis, there is no actual relationship between the SEQN values and the target classes of 'Adult' and 'Senior'.