Which three measurement levels are considered categorical fields? (Select three.)

Categorical fields are variables that represent categories or groups rather than numerical values. In the context of measurement levels, the two primary types of categorical data are nominal and ordinal.

Ordinal data is a type of categorical data where the categories can be ordered or ranked in a meaningful way, but the intervals between the ranks are not necessarily equal. For example, a rating scale (like "poor," "fair," "good," "excellent") provides a clear ranking among the categories, thus making it an ordinal measurement level.

Nominal data consists of categories that cannot be ordered or ranked. Examples include gender, race, or types of fruit. These categories are distinct and have no inherent ranking.

While a flag can represent a binary categorical field (e.g., yes/no), it may not be typically referred to as a distinct measurement level in the same sense as ordinal or nominal data. Continuous data, on the other hand, are numerical and not categorical, as they represent measurable quantities like height or weight.

Therefore, the accurate selection of ordinal and nominal highlights the nature of categorical fields correctly.