Based on prior knowledge, higher levels of plasma glucose concentration typically indicate diabetes.


To analyze the relationship between the Glucose feature and the task of determining whether a person has diabetes or not, we can consider the following approach:

1. Split the dataset into two groups based on the target variable: "yes" (indicating the presence of diabetes) and "no" (indicating the absence of diabetes).
2. Calculate the statistical measures (mean, median, mode, etc.) for the Glucose feature in each group.
3. Identify the typical Glucose values for each target class based on the statistical measures and any known thresholds or guidelines.

Here's the dictionary with the requested format:

```json
{
	"yes": [200.0, 220.0, 240.0, 250.0, 280.0],
	"no": [80.0, 90.0, 100.0, 110.0, 120.0]
}
```

Please note that the values provided in the dictionary are not based on any specific dataset or analysis, but rather serve as placeholders for typical Glucose values. The actual values should be determined based on the analysis of an appropriate dataset.