A nominal variable is a type of categorical variable used to label or categorize data into mutually exclusive groups that have no intrinsic order or ranking. These variables are qualitative in nature, meaning they do not possess any quantitative value or numerical properties, and arithmetic operations cannot be performed on them

. Key characteristics of nominal variables include:

• Categories are distinct and cannot be logically ordered or ranked (e.g., eye color, breed of dog, city names)

• They can be represented by names or numbers, but the numbers are merely labels without numeric meaning or hierarchy (e.g., 1 for brown hair, 2 for blonde hair, etc.)

• Nominal variables form the basis of the nominal scale of measurement, which is the simplest and least precise level of measurement

Examples of nominal variables:

• Hair color (black, brown, blonde)
• Types of transportation (car, bus, train)
• Political preferences (Democrat, Republican, Independent)
• Zip codes or student ID numbers (used as labels, not numeric values)

In summary, a nominal variable categorizes data without any order or ranking, serving primarily as labels or names for groups in qualitative data analysis