Which description best fits an interval variable?

An interval variable is best described as numerical data that lacks a true zero point. This means that while the intervals between values are meaningful and consistent, the zero value does not indicate the absence of the quantity being measured. For example, in temperature scales like Celsius and Fahrenheit, zero does not mean there is no temperature; instead, it is simply another point on the scale. This distinction is crucial because it highlights that interval data can be measured and compared, but one cannot make statements about ratios.

In contrast to interval variables, categorical data without rank cannot be ordered meaningfully, and numerical data with a true zero represents ratios and allows for statements such as "twice as much." Non-numeric data with rank may indicate order but does not quantify the differences in a meaningful way. Therefore, the characteristics of interval variables directly align with the description of numerical data lacking a true zero.