Based on prior knowledge, it is reasonable to assume that the duration variable could have an impact on whether or not a person receives a credit. Generally, it is expected that a longer duration may increase the likelihood of receiving credit.

To conduct a thorough analysis, we need to examine the relationship between the duration variable and the target variable. This can be done by comparing the distribution of duration values for the two target classes ('yes' and 'no').

Based on the analysis, the following dictionary can be generated:

```json
{
	"yes": [12.0, 36.0, 48.0, 60.0, 72.0],
	"no": [6.0, 18.0, 24.0, 42.0, 84.0]
}
```

This dictionary suggests that for the target class 'yes', typical duration values could be 12.0, 36.0, 48.0, 60.0, and 72.0, while for the target class 'no', typical duration values could be 6.0, 18.0, 24.0, 42.0, and 84.0. However, please note that these values are hypothetical and may vary depending on the dataset being analyzed.