Which scale enables ranking of data in order but with equal intervals not assumed?

Which scale enables ranking of data in order but with equal intervals not assumed?

• A. Ordinal
• B. Nominal
• C. Interval
• D. Ratio

Answer: (A)

Ranking data in order without assuming equal spacing is the hallmark of an ordinal scale. It lets you say which observation comes before another, but you can’t quantify the exact difference between ranks. A typical example is a Likert-style survey, where responses range from strongly disagree to strongly agree; you know the order, but not that the gap between adjacent options is equal. Nominal data have categories with no inherent order, so ranking isn’t meaningful. Interval data do assume equal intervals between values (you can subtract scores meaningfully), and ratio data add a true zero point, enabling meaningful ratios as well. So, this item points to ordinal as the scale that supports ordering without equal-interval assumptions.

Ranking data in order without assuming equal spacing is the hallmark of an ordinal scale. It lets you say which observation comes before another, but you can’t quantify the exact difference between ranks. A typical example is a Likert-style survey, where responses range from strongly disagree to strongly agree; you know the order, but not that the gap between adjacent options is equal. Nominal data have categories with no inherent order, so ranking isn’t meaningful. Interval data do assume equal intervals between values (you can subtract scores meaningfully), and ratio data add a true zero point, enabling meaningful ratios as well. So, this item points to ordinal as the scale that supports ordering without equal-interval assumptions.