Based on prior knowledge, we can analyze the relationship between the feature RIDAGEYR (Respondent's Age) and the target task of predicting whether a person belongs to the senior or non-senior age group.

Since the target variables are 'Senior' and 'Non-senior', we need to determine appropriate ranges of age values for these groups. Let's assume that anyone aged 65 and above belongs to the 'Senior' group, and anyone below 65 belongs to the 'Non-senior' group.

Now, let's create the dictionary as required:

```json
{
	"Adult": [21.0, 35.0, 45.0, 55.0, 63.0],
	"Senior": [67.0, 72.0, 78.0, 82.0, 88.0]
}
```

In the above snippet, we have provided 5 typical RIDAGEYR values for each target class. The values [21.0, 35.0, 45.0, 55.0, 63.0] represent typical age values for the 'Non-senior' group, and the values [67.0, 72.0, 78.0, 82.0, 88.0] represent typical age values for the 'Senior' group.