Based on prior knowledge, it is difficult to predict a person's creditworthiness solely based on their job category. However, we can still perform a basic analysis to explore the relationship between the job feature and the target variable of receiving credit.

To do this analysis, we will look at the distribution of job categories for both the 'yes' and 'no' classes of the target variable.

```json
{
	"yes": ["skilled", "unskilled resident", "high qualif/self emp/mgmt", "unemp/unskilled non res"],
	"no": ["skilled", "unskilled resident", "high qualif/self emp/mgmt", "unemp/unskilled non res"]
}
```

Based on the analysis, it appears that the job feature includes all possible values for both classes of the target variable. However, please note that this analysis does not indicate a strong relationship between the job feature and the credit decision.