Creating the data visualizations and table outputs

Data visualization is one of the most intuitive ways of presenting the data. Visual patterns are much easier to spot and describe compared to text or numbers. This is why the majority of high-quality research includes not just numerical but also visual representations of the data.

In the Diabetes dataset, we will be exploring the potential differences or similarities in the data distribution between diabetes and control subjects. We will explore their lipid profile (LDL, HDL, and TG) and HbA1c, a clinical measure used to show how much of the hemoglobin is glycated over a period of 3 months (a value that tells us the status of glucose over 3 months).

Before creating the visualizations, to simplify the process, create a new object that contains four variables: TG, LDL, HDL, and HbA1c. This object will be used to create data visualizations easily. Here is how we can do it:

#Create an object containing only 4 variables to analyze...