Nominal data is a type of non-numeric data set used in computing. It consists of variables that are organized into two or more categories, without any form of numerical order or ranking being assigned to each category. The designated categories are often represented through symbols, such as letters or numbers.
In information technology, numeric data and nominal data are two types of data that have different uses. Numeric data is used for calculations, such as mathematical equations, statistical analysis, and other forms of quantitative analysis. Nominal data is used when data is being organized or classified into predetermined and mutually exclusive categories. For example, a data set containing gender information would be a type of nominal data, with the categories consisting of male and female.
Nominal data is commonly used when data is qualitative rather than quantitative. It is useful for applications such as surveys, questionnaires, and focus groups. In these cases, the categories are created to reflect the characteristics of the different items being studied, and the data set is used to classify individual items of that type.
Nominal data sets can also be used when the end goal is to measure the classification accuracy of an algorithm, or when a data set needs to be converted to a numerical format in order to be further analyzed. A common example is when gender is encoded as the numbers 0 and 1, to be used as a variable for logistical regression.
Nominal data is a vital part of the data processing pipeline in many computing fields. Its uses range from analyzing survey data to validating the accuracy of automated classification algorithms. It is useful in many contexts for facilitating the analysis of data sets, especially when quantitative analysis is not the primary focus.
