👉 Over-normalized data refers to a set of data that is slightly less normalized than the original dataset. This means that some values are more concentrated than others, and the overall distribution of the data may not be as spread out as it would be if all values were equally likely. For example, consider a dataset where there are many outliers (values greater than 3 times the mean) in one group compared to the rest of the dataset. This can make the dataset look more "over-normalized"
