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

In general, it is expected that individuals who work longer hours per week tend to earn more than those who work fewer hours. However, this relationship may not hold true for all cases, as there could be other factors influencing income, such as the nature of the job, the industry, and the level of education.

To create the dictionary with the specific details, let's consider typical values for each target class:

```json
{
	"no": [10, 20, 25, 30, 35],
	"yes": [40, 45, 50, 55, 60]
}
```

In this case, we assume that individuals who earn less than 50000 dollars per year ("no" class) tend to have lower typical hours-per-week values, such as 10, 20, 25, 30, and 35. On the other hand, individuals who earn more than 50000 dollars per year ("yes" class) tend to have higher typical hours-per-week values, such as 40, 45, 50, 55, and 60.

Please note that these values are just examples and may not represent the actual distribution of hours-per-week for each target class. A more accurate analysis would require studying the dataset or conducting statistical analysis.