What are the 3 categorical variables?

In contrast, nominal variables represent categories that have no inherent ordering or ranking. These variables are used to label or classify observations into distinct groups. Examples of nominal variables include colors (red, blue, green), nationalities (American, British, Chinese), and blood types (A, B, AB, O).

Categorical variables play a significant role in data analysis and are classified into three distinct types: binary, nominal, and ordinal. Each type possesses unique characteristics that make them suitable for different analytical purposes.

Binary variables, also known as dichotomous variables, are the simplest form of categorical variables. They can take on only two possible values, typically represented as 0 and 1, or yes and no. Examples include gender (male/female), pregnancy status (yes/no), and the presence or absence of a particular characteristic.

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Ordinal variables, on the other hand, represent categories that have a natural ordering or ranking. Unlike nominal variables, the order of ordinal categories is meaningful and can be used to compare observations. Examples of ordinal variables include levels of satisfaction (very satisfied, satisfied, neutral, dissatisfied, very dissatisfied), educational attainment (elementary, middle school, high school, college, graduate degree), and rating scales (1-star, 2-stars, 3-stars, 4-stars, 5-stars).