We already know that we can identify data as being either qualitative or quantitative. But, from there, we can go further. The four levels of data are:
- The nominal level
- The ordinal level
- The interval level
- The ratio level
Each level comes with a varying level of control and mathematical possibilities. It is crucial to know which level data lives on because it will dictate the types of visualizations and operations you are allowed to perform.
The first level of data, the nominal level, has the weakest structure. It consists of data that are purely described by name. Basic examples include blood type (A, O, AB), species of animal, or names of people. These types of data are all qualitative.
Some other examples include:
- In the
SF Job Salary
dataset, theGrade
column would be nominal - Given visitor logs of a company, the first and last names of the visitors would be nominal
- Species of animals in a lab experiment would be nominal