What is the main focus of nominal measures?

Nominal measures focus primarily on categorizing data without involving any numerical measurement or ranking. They are used to classify data into distinct categories based on qualitative attributes. For example, nominal data can represent gender, hair color, or types of crimes. In these cases, the categories are mutually exclusive and exhaustive, meaning every data point can fit uniquely into one category without any implication of order or rank.

In contrast, options that suggest providing a ranking, measuring exact quantities, or determining interval scales pertain to other types of data measurement. Ranking implies an ordinal measure, which does provide a sense of order but does not quantify the differences between ranks. Measuring exact quantities pertains to ratio or interval data, which involves numerical values and a meaningful scale. Interval scales involve equal intervals between values, which is not applicable in nominal measurement. Therefore, the emphasis of nominal measures lies in classification rather than measurement or ranking.