It is generally understood that a specific characteristic (feature/column) of structured data can be broken down into one of four levels of data. The levels are:
The nominal level
The ordinal level
The interval level
The ratio level
As we move down the list, we gain more structure and, therefore, more returns from our analysis. Each level comes with its own accepted practice in measuring the center of the data. We usually think of the mean/average as being an acceptable form of center, however, this is only true for a specific type of data.
The first level of data, the nominal level, (which also sounds like the word name) consists of data that is described purely by name or category. Basic examples include gender, nationality, species, or yeast strain in a beer. They are not described by numbers and are therefore qualitative. The following are some examples:
A type of animal is on the nominal level of data. We may also say that if you are a chimpanzee, then...