Nonnumerical

Nonnumerical is an adjective that describes something that is not numerical or not composed of numbers. It is used to indicate that a value, data type, or concept does not involve numeric quantities or measurements in its intrinsic meaning.

In data analysis and statistics, the term often appears as nonnumerical data, also called qualitative data. Such data represent categories, labels, or attributes rather than numeric quantities and are typically processed through frequency counts, categorization, or encoding rather than arithmetic operations. Examples include colors, genres, names, and survey responses like yes/no or preferences.

In computing and data representation, nonnumerical values encompass types such as strings (text), characters, booleans, and enumerations. The exact classification can depend on the programming language: some languages treat booleans as separate types, while others allow them to be used in numeric expressions under certain rules. In databases, nonnumerical fields often use text, date, or categorical types, contrasted with numeric fields used for quantities, prices, or counts.

The term can be used with or without a hyphen, as nonnumeric or non-numerical or non-numerical; the preferred form varies by style guide. A related concept is qualitative versus quantitative data, where nonnumerical data are not measured on a numeric scale. Coded representations can blur this distinction when categories are assigned numeric codes, even though the underlying data remain nonnumerical in meaning.

Overall, nonnumerical highlights the distinction between what can be counted or measured numerically and what is described by names, categories, or qualitative attributes.