Author: Ernad Mujakic
Date: 2025-07-07

Nominal data is a type of Categorical Data that represents categories that don't have a specific order or ranking. Unlike Ordinal Data, which has a defined order, nominal data is purely qualitative. It describes specific qualities without conveying any measure of numerical significance.

Since nominal data lacks numerical significance, data operations such as Mean or Median cannot be performed. However, the frequency of nominal data values can be analyzed, and a measure like the Mode can describe the most common category within a given dataset.

A specific type of nominal data is Binary Data, which consists of only two categories, typically represented as 1 and 0. Binary fields are commonly used to represent whether a certain feature is present or not in a given data object.

Examples of nominal data include attributes like eye color (e.g., blue, brown, green), gender (e.g., male, female, non-binary), and nationality (e.g., American, Canadian). These categories do not imply any hierarchy or order.

Nominal data, lacking any numerical significance, primarily relies on frequency distribution analysis for meaningful insights. One of the most effective techniques for this is the use of a Bar Chart, which visually represent the frequency of each category.