Based on prior knowledge, it is generally expected that higher levels of education tend to be positively correlated with higher income. However, it is important to conduct a thorough analysis to confirm this relationship. 

To analyze the relationship between education and the target variable (earning more than 50000 dollars per year), we can examine the distribution of education levels within each target class.

Here is the dictionary analysis of the relationship between the "education" feature and the target variable:

```json
{
	"no": [
		"11th",
		"HS-grad",
		"Some-college",
		"10th",
		"7th-8th",
		"9th",
		"12th",
		"1st-4th",
		"Preschool"
	],
	"yes": [
		"Assoc-acdm",
		"Prof-school",
		"Bachelors",
		"Masters",
		"Doctorate",
		"5th-6th",
		"Assoc-voc"
	]
}
```

Based on the analysis, individuals with education levels of "Assoc-acdm", "Prof-school", "Bachelors", "Masters", "Doctorate", "5th-6th", and "Assoc-voc" are more likely to earn more than 50000 dollars per year. Conversely, individuals with education levels of "11th", "HS-grad", "Some-college", "10th", "7th-8th", "9th", "12th", "1st-4th", and "Preschool" are less likely to earn more than 50000 dollars per year. Please note that this analysis assumes no additional context or external factors beyond the education level feature.