What is nominal data?

Nominal data refers to a type of data that is used for labeling variables without implying any quantitative value. In this context, the correct answer points to data that is categorized with arbitrary codes. For example, nominal data includes categories such as gender (male, female), colors (red, blue, green), or types of animals (dog, cat). Each of these categories is distinct and does not have a natural order or ranking.

The emphasis on "arbitrary codes" suggests that the numbers or labels assigned to these categories do not carry value or significance beyond identifying the groups themselves. This is characteristic of nominal data, as it serves primarily to distinguish between different classifications or groups rather than to convey information about quantities or order.

The other choices refer to different types of data. Data with a logical order characterizes ordinal data, which ranks categories based on some scale (e.g., ratings such as poor, fair, good). Numeric scales describe interval or ratio data, which involve measurable quantities. Finally, data that represents percentages generally refers to proportions derived from quantitative data, making it a different category of measurement altogether. Thus, the focus on arbitrary categorization in nominal data highlights its unique role in data classification within GIS and other fields.