Based on prior knowledge, it is known that there can be a relationship between a person's race and their income level. However, it is important to note that making assumptions about a person's income based on their race is not appropriate and can perpetuate stereotypes. Income levels can vary greatly within each racial group, and it is important to consider other factors such as education, occupation, and experience.

To complete the analysis, we can look at the distribution of income levels within each racial category and analyze the relationship between race and income.

Possible values of the feature race for the target class "no" (earning less than or equal to 50000 dollars per year) and the target class "yes" (earning more than 50000 dollars per year) can be determined by analyzing the dataset or conducting a statistical analysis. However, without access to the dataset or specific information on the frequency of each race category, it is hard to provide a specific analysis.

Here is a general dictionary structure based on the racial categories provided:

```json
{
	"no": ["Black", "White", "Asian-Pac-Islander", "Other", "Amer-Indian-Eskimo"],
	"yes": ["Black", "White", "Asian-Pac-Islander", "Other", "Amer-Indian-Eskimo"]
}
```

Please note that this dictionary assumes that each racial category is represented in both the "no" and "yes" target classes. Further analysis would be required to determine the distribution of race within each income level category.