Based on prior knowledge and common understanding, there is a general perception that a person's age can be related to their income level. Younger individuals are often in the early stages of their careers and may not yet have reached higher earning potential, while older individuals may have more experience and higher salaries. 

To analyze the relationship between age and the target variable of earning more than $50,000 per year, we can assume that there might be a larger proportion of individuals who earn less than $50,000 in the younger age range, as they are likely to be in the early stages of their careers. On the other hand, individuals in the older age range might have a higher likelihood of earning more than $50,000, as they may have had more time to advance in their careers.

Based on this analysis, the dictionary with the specific details can be generated as follows:

```json
{
	"no": [18, 19, 20, 21, 22],
	"yes": [35, 40, 45, 50, 55]
}
```

In this dictionary, the "no" class represents individuals who earn less than $50,000 per year, and the "yes" class represents individuals who earn more than $50,000 per year. The age values provided are just examples and can be adjusted based on the specific dataset or domain knowledge.