Based on my prior knowledge, the feature 'hours-per-week' can potentially have a significant relationship with the target variable 'Does this person earn more than 50000 dollars per year?'.

Let's conduct a thorough analysis:

1. Individuals who work full-time typically work 40 hours per week or more. Hence, it is logical to assume that individuals working more than 40 hours per week would have a higher chance of earning more than $50,000 per year. 
2. On the other hand, individuals who work fewer hours per week, particularly those working part-time or who have irregular working hours, might have a lower chance of earning more than $50,000 per year.

Based on this analysis, let's create the dictionary:

```json
{
	"no": [10, 15, 20, 25, 30],  
	"yes": [45, 50, 55, 60, 65]
}
```

In this example, we assume that individuals working less than 40 hours per week are less likely to earn more than $50,000 per year ('no' class), while individuals working more than 40 hours per week have a higher chance of earning more than $50,000 per year ('yes' class). The values in the lists represent typical hours-per-week values for each target class.