Categorical Variable vs Nominal Variable
Both terms below come up in the same part of the course, and students mix them up. Here is each one defined on its own, side by side, so you can see where they part company.
Categorical variable
Variables and data types
A categorical variable records which group or category an individual belongs to, rather than a numerical measurement.
The values of a categorical variable are labels, so arithmetic like averaging them has no meaning. For example, eye color with values blue, brown, and green is categorical, as are yes or no answers. You summarize categorical data with counts and proportions, and display it with bar graphs. If 30 of 120 people have blue eyes, the proportion is , or 25 percent.
Nominal variable
Variables and data types
A nominal variable is a categorical variable whose categories have no natural order, such as blood type, eye color, or brand of phone.
The values of a nominal variable are pure labels, so you can count them and name the most common one, but ranking or averaging them means nothing. For example, blood types A, B, and O among 100 donors with counts 20, 15, and 65 give a mode of O at , and there is no such thing as a median blood type. The AP Statistics course framework does not use the words nominal or ordinal; it groups both under categorical variables, also called qualitative variables. Treat the split as useful college vocabulary rather than tested AP content.