A qualitative variable, also known as a categorical variable, is a type of variable in statistics that describes an attribute or characteristic of a data point, rather than a numerical value. Qualitative variables are typically represented by labels or categories and are used to categorize data into distinct groups based on non-numerical characteristics or attributes. They can be further classified as nominal, ordinal, or dichotomous.

• Nominal variables: These variables have two or more categories that have "names," not numerical values. They have no natural or intrinsic order to them. Examples of nominal variables include eye color (blue, green, brown, hazel), states (Florida, New Jersey, Washington), and dog breeds (Alaskan Malamute, German Shepherd, Siberian Husky, Shih Tzu).
• Ordinal variables: These variables have categories that can be ordered or ranked, but the differences between the categories may not be equal. For example, a Likert scale with options such as "strongly agree," "agree," "neutral," "disagree," and "strongly disagree" is an ordinal variable.
• Dichotomous variables: These variables have only two categories. Examples include yes/no, true/false, and success/failure.

Qualitative variables are often used in various fields, including healthcare research, social sciences, and market research, to gather information about a populations characteristics, identify risk factors, and evaluate the effectiveness of different treatments or interventions.