Based on prior knowledge, higher levels of education are generally associated with higher income levels. Therefore, it is reasonable to assume that individuals with higher educational-num values are more likely to earn more than 50000 dollars per year.

To analyze the relationship between the feature educational-num and the target task of earning more than 50000 dollars per year, we can examine the distribution of educational-num values for both target classes.

Here is the analysis and the corresponding dictionary:

```json
{
	"no": [1, 2, 3, 4, 5],
	"yes": [10, 11, 12, 13, 14]
}
```

Explanation:

- Target class 'no': Based on the analysis, a list of possible educational-num values for individuals who earn less than or equal to 50000 dollars per year includes [1, 2, 3, 4, 5]. These values represent lower levels of education.
- Target class 'yes': From the analysis, a list of possible educational-num values for individuals who earn more than 50000 dollars per year includes [10, 11, 12, 13, 14]. These values represent higher levels of education.

Please note that the educational-num values provided are just examples and may not cover the entire range of possible values. The specific values may vary depending on the dataset and its distribution.