Based on prior knowledge, we can assume that senior individuals are typically 65 years of age or older. Therefore, we can categorize individuals as either senior or non-senior based on their age.

To analyze the relationship between the feature "RIAGENDR" (Respondent's Gender) and the target variable "age group" (senior or non-senior), we can examine the distribution of gender values for each age group.

Here is a dictionary that showcases the typical RIAGENDR values for each target class:

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

In this case, the "Adult" class represents non-senior individuals, and the "Senior" class represents senior individuals. The dictionary provides five typical values for "RIAGENDR" in each of the target classes. Note that the RIAGENDR values are presented as floats within the lists.