Analysis:
To analyze the relationship between the feature LBXGLU (Respondent's Blood Glucose after fasting) and the target variable age group (Senior or non-senior), we can make some assumptions based on prior knowledge.

1. Generally, higher blood glucose levels are more likely to be associated with older individuals.
2. The threshold for defining high blood glucose levels might vary for different age groups.
3. The blood glucose levels for seniors might have a wider range compared to non-seniors, as it is common for blood glucose levels to increase with age.

Based on these assumptions, we can expect that the feature LBXGLU will have higher values on average for the target class "Senior", compared to "Adult" class.

Based on the provided feature description, we should use our prior knowledge to determine appropriate ranges of values for "Adult" and "Senior" classes.

Dictionary:
```json
{
	"Adult": [80.0, 85.0, 90.0, 95.0, 100.0],
	"Senior": [90.0, 95.0, 100.0, 105.0, 110.0]
}
```

Note: The values provided in the dictionary are just placeholders and should be replaced with actual values that reflect the specifics of the dataset.