Based on my prior knowledge, I will analyze the relationship between the feature BMXBMI and the target task of predicting the person's age group.

Generally, BMI is a measure of body fat based on an individual's weight and height. It is calculated by dividing the weight in kilograms by the square of the height in meters. The BMI provides an estimation of a person's overall body fatness.

To determine the appropriate ranges of BMXBMI values for the age groups, it would be helpful to consider the World Health Organization (WHO) classification of BMI categories:

- Underweight: Below 18.5
- Normal weight: 18.5 - 24.9
- Overweight: 25 - 29.9
- Obesity class I: 30 - 34.9
- Obesity class II: 35 - 39.9
- Obesity class III: 40 and above

Since the task is to predict if a person is a senior or not, I would assume that individuals aged 65 or above are classified as seniors. Therefore, I will consider the BMXBMI values for these age groups.

Based on the analysis, I will generate a dictionary with the possible values of BMXBMI for each target class:

```json
{
	"Adult": [18.5, 21.3, 23.8, 26.4, 29.1],
	"Senior": [20.1, 22.7, 25.6, 28.3, 31.2]
}
```

Please note that the provided BMXBMI values are just hypothetical examples and should not be considered as absolute values for categorizing individuals into specific target classes. The actual classification should be done using appropriate classification models and considering a larger dataset.