What does the term categorical imply in data analysis?

In data analysis, the term "categorical" refers to variables that are divided into distinct categories that do not overlap. The correct choice highlights that categorical data consists of distinct groups or classifications where each observation belongs to one specific category.

This means that categorical data can represent characteristics such as gender, color, or type of car, where each of these categories stands alone without any numerical value assigned to represent an order or measure. Unlike continuous variables, which can take any value within a range and show a continuous distribution, categorical variables are limited to specific groups.

Categories can be nominal, where there's no inherent order (e.g., red, blue, green), or ordinal, where a ranking can exist (e.g., satisfaction levels: low, medium, high). The defining feature of categorical data is the discrete nature of its categories, making option B the most accurate representation of the term in the context of data analysis.