Based on prior knowledge, let's assume that the age range for seniors starts from 65 years and above. Any age below 65 will be considered as non-senior in this analysis.

To analyze the relationship between the feature RIDAGEYR and the target task of predicting age group (senior or non-senior), we can group the respondents' age into two categories: Adult and Senior.

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

```json
{
    "Adult": [18.0, 25.0, 32.0, 40.0, 50.0],
    "Senior": [70.0, 75.0, 80.0, 85.0, 90.0]
}
```

In this dictionary, for the target class "Adult," we have selected 5 typical values of RIDAGEYR as [18.0, 25.0, 32.0, 40.0, 50.0]. Similarly, for the target class "Senior," we have chosen 5 typical values of RIDAGEYR as [70.0, 75.0, 80.0, 85.0, 90.0].

These values are just examples and may not represent the actual distribution of the data, but they provide a general understanding of the relationship between RIDAGEYR and the age group prediction task based on prior knowledge.