The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
A set of data measured using the ratio scale takes care of the ratio problem and provides complete information. Ratio scale data are like interval scale data, except they have a zero point and ratios can be calculated. For example, four Statistics final exam scores are 80, 68, 20, and 92 (out of a possible 100 points). The exams are machine-graded. The data can be ordered from lowest to highest: 20, 68, 80, 92. The differences between the data values hold meaning. The score of 92 is greater than 68 by 24 points. Therefore, ratios can be calculated. For example, 80 is four times 20. Thus, a score of 80 is four times better than the score of 20. Also, the smallest possible score is 0.
In summary, the ratio level of measurement is an extension of the interval level of measurement. It includes data with a natural zero point, and the difference between the values and the ratio of values is meaningful.
This text is adapted from Openstax, Introductory Statistics, Section 1.2 Data, Sampling, and Variation in Data and Sampling
