Based on the given feature "LBXGLT" and the task of predicting a person's age group as either Senior or non-Senior, we will analyze the relationship between the feature and the target variable.

Since no information is provided about the feature "LBXGLT", we will assume that it represents a numeric variable. To determine the appropriate ranges of values, we may need more details or domain expertise. However, for demonstration purposes, I will provide an analysis based on a hypothetical scenario.

Assuming that "LBXGLT" represents a laboratory blood test value for glucose levels, we can hypothesize that higher glucose levels may be associated with senior age group due to conditions like diabetes. At the same time, lower glucose levels may be more typical for non-senior individuals.

Here is the dictionary with 5 typical values for each age group:

```json
{
	"Adult": [90.3, 92.1, 95.7, 98.5, 100.2],
	"Senior": [105.8, 108.6, 110.4, 114.2, 116.9]
}
```

Please note that this analysis is based on a hypothetical scenario, and without further information, it is difficult to determine the exact relationship between the feature "LBXGLT" and the age group. Additionally, the appropriate ranges and interpretation may differ based on the specific context and domain expertise.