Based on prior knowledge, we can expect the feature "hours-per-week" to have some relationship with the target variable "Does this person earn more than 50000 dollars per year?". Typically, individuals who work longer hours per week tend to earn more money. However, it is also important to consider that some individuals may have other factors influencing their earnings, such as the hourly rate or the type of work they perform.

To analyze the relationship between the feature and the task, we can start by checking the distribution of "hours-per-week" for each target class and identify typical hour values.

Here is the analysis and the resulting dictionary:

```json
{
	"no": [1, 10, 20, 30, 40], 
	"yes": [35, 45, 50, 55, 60]
}
```

Explanation:
- For the target class "no" (individuals earning less than or equal to 50000 dollars per year):
  - Typical hours-per-week values could be [1, 10, 20, 30, 40]. This range includes individuals who may work part-time, work reduced hours, or have multiple jobs.
- For the target class "yes" (individuals earning more than 50000 dollars per year):
  - Typical hours-per-week values could be [35, 45, 50, 55, 60]. This range includes individuals who may work full-time or have additional overtime hours.

Please note that these values are just examples and may vary in different datasets or scenarios. A more comprehensive analysis could be done using statistical techniques to identify the ranges based on the dataset's specific characteristics.