Based on prior knowledge, we can analyze how the feature LBXIN (Respondent's Blood Insulin Levels) relates to the task of predicting the person's age group (Senior or non-senior).

The relationship between LBXIN and age group can vary depending on various factors, including the individual's health status, lifestyle, and underlying medical conditions. However, in general, insulin levels tend to increase with age. Thus, it is reasonable to assume that higher LBXIN values may be more common in the Senior age group compared to the non-senior age group.

To create the dictionary, we can identify typical LBXIN values for each target class, 'Adult' and 'Senior'. Let's assume the following ranges for the age groups:

- 'Adult': 18 to 59 years
- 'Senior': 60 years and above

Here is a dictionary with 5 typical LBXIN values for each target class:

```json
{
	"Adult": [4.5, 5.2, 3.8, 4.9, 5.7],
	"Senior": [6.1, 7.3, 5.5, 6.8, 5.9]
}
```

Please note that the LBXIN values provided are just placeholders and do not represent actual values. You can replace them with appropriate numeric values based on your dataset or context.