Based on prior knowledge, we can analyze the relationship between the feature "hours-per-week" and the task of whether a person earns more than $50,000 per year.

In general, we can make the following assumptions:
- People who work fewer hours per week are less likely to earn more than $50,000 per year as they have less time to generate income.
- People who work more hours per week may have a higher chance of earning more than $50,000 per year as they have more opportunities to generate income.

Now, let's create a dictionary with the possible values of the "hours-per-week" feature for each target class ("no" and "yes"):

```json
{
  "no": [20, 25, 30, 35, 40],
  "yes": [45, 50, 55, 60, 65]
}
```

Note that the values provided above are just examples and may not represent the actual distribution of "hours-per-week" for each target class accurately. It is always essential to analyze the actual dataset to determine the ranges and typical values of features for each class.