The nominal scale, sometimes called the qualitative type, places non-numerical data into categories or classifications. For example:
- A Persian is a breed of cat.
- Jacksonville is a city in Florida.
Both of those pieces of information aren’t numerical and so are assigned a category (breeds of cat and cities in Florida). Qualitative variables are measured on the nominal scale.
Mean Mode and Median for the Nominal Scale
The nominal scale uses categories, so finding the mean or the median makes no sense. You could put the items in alphabetical order but even then, the middle item would have no meaning as a median. However, a mode (the most frequent item in the set) is possible. For example, if you were to survey a group of random people and ask them what the most romantic city in the World is, Venice or Paris might be the most common response (the mode).
Nominal Scale Examples
- Counting how many people help someone else in a set-up scene (like the TV show “What Would You Do?“.
- Surveying people to find out if men or women have higher self-esteem.
- Finding out if introverts or extroverts are more likely to be philanthropic.
The nominal scale is one of four scales of measurement in statistics. The other three are:
- The Ordinal Scale: Rank order (1st, 2nd 3rd), dichotomous data that has two choices like true/false or guilty/innocent and non-dichotomous data with choices like “completely agree” “somewhat agree” “neutral” and “disagree.”
- The Interval Scale, sometimes called Scaled Variable: data with degrees of difference like time B.C. or Celsius.. Interval scales have arbitrary zeros (when B.C. began and ended has no real mathematical basis).
- The Ratio Scale: encompasses most measurements in physics and engineering like mass and energy. Ratio scales have meaningful zeros (zero energy means that energy does not exist).
The four scales were suggested by Stanley Smith Stevens in a 1946 Science article titled “On the Theory of Scales of Measurement.”