Based on the given feature description and task, we are trying to predict whether a person is a senior or non-senior based on their engagement in moderate or vigorous-intensity sports, fitness, or recreational activities in a typical week.

To analyze the relationship between the feature (PAQ605) and the target (Age Group), we can use our prior knowledge to determine the appropriate ranges of values. Let's assume that a higher value of PAQ605 represents a higher level of engagement in physical activities.

Here is the analysis:

- Adult Age Group: People in this age group are typically younger and more physically active. It is likely that a higher percentage of adults will engage in moderate or vigorous-intensity physical activities. Therefore, we can expect higher values of PAQ605 for the Adult age group. 

- Senior Age Group: People in this age group are typically older and may have lower levels of physical activity compared to adults. Consequently, we can expect lower values of PAQ605 for the Senior age group.

Based on this analysis, we can create a dictionary with the requested format:

```json
{
	"Adult": [1.0, 1.0, 1.0, 1.0, 1.0], 
	"Senior": [2.0, 2.0, 2.0, 2.0, 2.0]
}
```

Note: The dictionary includes 5 typical values for each target class ['Adult', 'Senior']. The values provided are examples, and the actual data might vary.