Arizona State University (ASU) STP226 Elements of Statistics Exam 1 Practice

Nominal variables are those that classify data into distinct categories that do not have a natural order or ranking. For example, variables such as gender, hair color, or types of cuisine are all nominal because each category is simply different from the others, without any kind of hierarchy or quantitative relationship between them.

In contrast, ordinal variables do have a ranking or order associated with them, such as socioeconomic status (low, medium, high) or satisfaction levels (satisfied, neutral, dissatisfied). Interval variables and ratio variables, on the other hand, are types of quantitative variables where numerical values can be manipulated arithmetically. Interval variables have meaningful differences between values but no true zero point (like temperature in Celsius), while ratio variables have both meaningful differences and a true zero point (like height or weight).

Thus, the classification of qualitative variables shows that nominal variables stand apart because they capture categories without any implied order.