Based on prior knowledge, we can analyze the relationship between the feature "RIAGENDR" (Respondent's Gender) and the task of predicting the age group (Senior or non-senior).

Typically, the age range for adults is considered to be below 65, while the age range for seniors is generally considered to be 65 and above. Therefore, we can assume that individuals with an age between 18 and 64 are categorized as non-seniors (Adult), and those with an age of 65 and above are classified as seniors.

From the feature "RIAGENDR", which represents the respondent's gender, we can infer that the possible values are 1 for Male and 2 for Female.

Based on this analysis, we can create the following dictionary:

```json
{
	"Adult": [1.0, 1.0, 2.0, 2.0, 2.0], 
	"Senior": [1.0, 1.0, 1.0, 2.0, 2.0]
}
```

In this dictionary, the "Adult" class has five typical values for the feature "RIAGENDR", which are 1.0 (Male) and 2.0 (Female). Similarly, the "Senior" class also has five typical values, with a value of 1.0 representing Male and 2.0 representing Female.

Please note that the actual data may have more unique values, but we have provided five typical values for each class as examples.