Based on prior knowledge, the occupation of an individual can be a significant factor in determining whether they earn more than $50000 per year. Some occupations tend to be higher paying than others, so it is likely that certain occupation categories will have a higher proportion of individuals earning more than $50000.

To analyze the relationship between occupation and the target variable, we can take a look at the distribution of occupations for individuals who earn more than $50000 versus those who do not.

Based on this analysis, we can create the following dictionary:

```json
{
    "no": ["Machine-op-inspct", "Farming-fishing", "?", "Other-service", "Priv-house-serv", "Armed-Forces"],
    "yes": ["Protective-serv", "Prof-specialty", "Exec-managerial", "Tech-support", "Sales", "Craft-repair", "Adm-clerical", "Transport-moving", "Handlers-cleaners"]
}
```

This means that individuals in the occupation categories "Machine-op-inspct", "Farming-fishing", "?", "Other-service", "Priv-house-serv", and "Armed-Forces" are more likely to earn less than $50000 per year. On the other hand, individuals in the occupation categories "Protective-serv", "Prof-specialty", "Exec-managerial", "Tech-support", "Sales", "Craft-repair", "Adm-clerical", "Transport-moving", and "Handlers-cleaners" are more likely to earn more than $50000 per year.

Please note that the occupation category "?" has been included in both lists as it represents missing or unknown occupation values.