Which statement correctly characterizes interval level data?

Which statement correctly characterizes interval level data?

• A. Interval data have ordered categories with equal intervals but no true zero.
• B. Interval data require a true zero to compare ratios.
• C. Interval data are qualitative categories.
• D. Interval data are counts.

Answer: (A)

Interval level data are numeric values that have a meaningful order and equal spacing between adjacent values, but the zero point is arbitrary and does not indicate the absence of the quantity. Because zero isn’t a true absence, you can add or subtract values and talk about differences, but you cannot meaningfully form ratios like twice as much. For example, with Celsius temperatures, the difference between 30° and 20° is the same interval as between 20° and 10°, yet 60° is not twice 30° in any meaningful sense. This matches the statement that interval data have ordered values with equal intervals but no true zero. The other descriptions refer to data with a true zero that allow ratios, or to qualitative categories or counts, which aren’t interval data.

Interval level data are numeric values that have a meaningful order and equal spacing between adjacent values, but the zero point is arbitrary and does not indicate the absence of the quantity. Because zero isn’t a true absence, you can add or subtract values and talk about differences, but you cannot meaningfully form ratios like twice as much. For example, with Celsius temperatures, the difference between 30° and 20° is the same interval as between 20° and 10°, yet 60° is not twice 30° in any meaningful sense. This matches the statement that interval data have ordered values with equal intervals but no true zero. The other descriptions refer to data with a true zero that allow ratios, or to qualitative categories or counts, which aren’t interval data.