Based on prior knowledge, it is generally understood that individuals who work more hours per week have a higher likelihood of earning more than $50,000 per year. However, it is important to conduct a thorough analysis to determine the specific relationship between the "hours-per-week" feature and the "earnings" target variable.

To analyze the relationship, we can examine the distribution of "hours-per-week" for each target class and identify typical values that are associated with each class.

Here is the dictionary that represents the analysis:

```json
{
	"no": [1, 2, 3, 4, 5],  
	"yes": [45, 50, 55, 60, 65]
}
```

In the "no" class, which indicates individuals who earn less than or equal to $50,000 per year, typical hours-per-week values could be 1, 2, 3, 4, and 5. These values suggest that some individuals in this class may work very few hours per week.

In the "yes" class, which indicates individuals who earn more than $50,000 per year, typical hours-per-week values could be 45, 50, 55, 60, and 65. These values indicate that individuals in this class tend to work more hours per week.

It is essential to note that these typical values are suggestions based on the general understanding of the relationship between hours-per-week and earnings. Further analysis using statistical techniques can provide more accurate insights into the relationship between this feature and the task.