Based on prior knowledge, we can analyze the relationship between the feature "hours-per-week" and the target variable "Does this person earn more than 50000 dollars per year?".

Typically, individuals who work more hours per week tend to earn more money. Therefore, it is expected that individuals who work more than a certain threshold of hours per week will have a higher likelihood of earning more than 50000 dollars per year.

Based on this analysis, we can create a dictionary as follows:

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

This dictionary suggests some typical values for "hours-per-week" for each target class. In the "no" class (those who earn less than 50000 dollars per year), individuals tend to work around 20 to 40 hours per week. In the "yes" class (those who earn more than 50000 dollars per year), individuals tend to work around 40 to 60 hours per week.

Please note that these values should be considered as generalizations and may vary based on the specific dataset being analyzed.