For effective statistical analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.

Data measured using the interval scale are similar to ordinal level data because they have a definite arrangement. However, in the interval level of measurement, the differences between data values are meaningful even though the data does not have a starting point.

Temperature is measured using the interval scale. It is measurable data, and the difference between the two temperature points is meaningful. Forty degrees equals 100 degrees minus 60 degrees. However, zero degrees does not mean that there is no temperature; it is just cold. Temperatures like −10 °F and −15 °C exist and are colder than zero.

Interval level data can be used in calculations, but the data cannot be compared. For example, 80 °C is not four times as hot as 20 °C (nor is 80 °F four times as hot as 20 °F). There is no meaning to the ratio of values in the interval level of measurement.

This text is adapted from Openstax, Introductory Statistics, Section 1.3 Frequency, Frequency Tables, and Levels of Measurement