Ordinal

Ordinal refers to a type of categorical variable where the categories have a natural order or ranking. In data science, ordinal variables are commonly used in statistical modeling and machine learning algorithms. Ordinal variables can be either discrete or continuous, and they are often represented by integers or numerical codes that reflect the order of the categories. Examples of ordinal variables include education level (e.g. high school, college, graduate school), income level (e.g. low, medium, high), and customer satisfaction rating (e.g. very dissatisfied, somewhat dissatisfied, neutral, somewhat satisfied, very satisfied). Ordinal variables are different from nominal variables, which have no natural order or ranking, and from interval/ratio variables, which have a fixed and measurable distance between values.
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