Based on my prior knowledge, I can analyze the relationship between the feature LBXIN (Respondent's Blood Insulin Levels) and the task of predicting the person's age group. 

Generally, as individuals age, their insulin levels tend to increase. However, the specific ranges of values for LBXIN that differentiate between the age groups of 'Adult' and 'Senior' will vary depending on the population being analyzed.

To create the dictionary with the requested format, I will assume the following LBXIN ranges:
- LBXIN values below 10 will be considered as 'Adult'.
- LBXIN values from 10 to 20 will be considered as 'Senior'.

Based on these assumptions, the dictionary can be structured as follows:

```json
{
	"Adult": [8.2, 9.5, 7.1, 6.4, 8.9],
	"Senior": [11.3, 14.2, 12.8, 10.6, 13.9]
}
```

Please note that these values are for illustrative purposes only, and the actual ranges may vary depending on the specific dataset and population being analyzed.