Based on prior knowledge, let's conduct a thorough analysis of the relationship between the age feature and the task of whether a person earns more than 50000 dollars per year.

Typically, younger adults may be more likely to earn less than 50000 dollars per year while older adults may be more likely to earn more than 50000 dollars per year. However, it's important to consider that this relationship can vary depending on other factors such as education, occupation, and location.

Now, let's create a dictionary with the age values for each target class:

```json
{
    "no": [20, 25, 30, 35, 40], 
    "yes": [45, 50, 55, 60, 65]
}
```

In this dictionary, we have listed 5 typical age values for each target class ('no' and 'yes'). These values are just examples and can vary depending on the specific dataset and its distribution.