Nominal Variable vs Ordinal 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.
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.
Ordinal variable
Variables and data types
An ordinal variable is a categorical variable whose categories have a meaningful order, but with no fixed numeric distance between them.
Ordering the categories of an ordinal variable is meaningful, so you can rank responses and report a median category, but the gaps between neighboring categories are not measured amounts. For example, 9 survey answers of poor, fair, good, and excellent with counts 2, 2, 3, and 2 put the 5th answer in order at good, so good is the median response, while averaging the four labels would mean nothing. The AP Statistics course framework does not use the words nominal or ordinal; both kinds count simply as categorical variables there. The distinction still matters in practice, because it decides whether reporting a median is fair game.