To analyze the relationship between the feature LBXGLU (Respondent's Blood Glucose after fasting) and the target task of predicting age group (Senior or non-Senior), we can use prior knowledge to determine appropriate ranges of values.

Prior knowledge suggests that higher blood glucose levels may be associated with increased age-related health issues such as diabetes. Therefore, we can assume that seniors may generally have higher blood glucose levels compared to non-seniors.

Based on this analysis, we can create a dictionary with lists of LBXGLU values for each target class:

```json
{
	"Adult": [80.5, 82.3, 85.9, 88.2, 89.7],
	"Senior": [92.1, 95.6, 97.3, 100.2, 104.8]
}
```

Please note that the specific LBXGLU values provided in the dictionary are just examples and may not represent actual values. The purpose of the dictionary is to demonstrate the expected format and provide a general understanding of the relationship between LBXGLU and the target age group.