What distinguishes ordinal variables from nominal ones?

Question

BlackTom AI · Accepted Answer

Question restatement: What distinguishes ordinal variables from nominal ones?

Option 1: They include decimal points. This is not a defining feature of ordinal variables; including decimal points is about the measurement scale (continuous vs categorical) and is not what makes a variable ordinal. Decimal points pertain more to measurement precision, not the core property of order.

Option 2: They imply order or ranking. This is the key distinguishing trait: ordinal variables convey a meaningful sequence (e.g., Likert scale levels like agree, neutral, disagree; education levels like high school, bachelor’s, master’s). The order matters, but the exact differences between adjacent levels are not necessarily equal.

Option 3: They are not used in surveys. This is false because both nominal and ordinal variables are commonly used in surveys to capture categorical responses. The statement mischaracterizes their usage.

Option 4: Ordinal variables are always numeric. This is incorrect because ordinal data can be categorical with a natural order that is not numeric (e.g., grade levels like A, B, C or rankings like first, second, third). Not all ordinal data are numbers, and even when numbers appear, they don’t always represent equal intervals.

Summary: Option 2 correctly captures the defining feature of ordinal variables—an inherent order or ranking—while the other options describe characteristics that do not apply or are misleading about ordinal data.

What distinguishes ordinal variables from nominal ones?

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