Based on the given feature description and task, we need to analyze how the feature SEQN relates to the target variable, which is the age group ('Senior' or 'Non-Senior'). Since there is no additional information provided about the feature, we will assume that SEQN represents a unique identifier for each respondent.

To analyze the relationship between SEQN and the age group, we would need access to a dataset that includes both the SEQN values and the corresponding age groups for each respondent. Without this dataset, it is not possible to determine how SEQN relates to the age group.

However, in order to provide a sample dictionary as requested, we can generate a random sample of SEQN values for each target class. Please note that this is just a random sample and does not represent the true relationship between SEQN and the age group.

```json
{
	"Adult": [1000.0, 2000.0, 3000.0, 4000.0, 5000.0],
	"Senior": [6000.0, 7000.0, 8000.0, 9000.0, 10000.0]
}
```

Again, it's important to note that without the actual dataset or more information about how SEQN relates to the age group, this random sample may not reflect the true relationship between the feature and target variable.