Quantitative variables (also called continuous variables) are an expression of a measure and are presented in the form of numerical data. Some examples of quantitative variables are temperature, pressure, and humidity values of a precise location. Quantitative variables can be further categorized as either interval or ratio variables.

Interval variables are variables that assume numeric values ​​that allow comparisons only by difference. It follows that it is possible to order statistical units based on the answers and also to measure the difference between the values ​​assumed by each of them. Interval scale assumes an arbitrary zero that represents a convention and not the absolute absence of the phenomenon (for example, temperature measured in degrees Celsius). In this case, you can compare the differences between temperatures but not the ratios:

• New York 10 °C
• Miami 20 °C
• Mexico City 30 °C

The difference between the temperature of Mexico City and Miami is the same difference as between Miami and New York (10 degrees), but the ratio is different.

Ratio variables are variables that assume numeric values ​​that allow comparisons for both the difference and the relationship between the modes that the units assume. It follows that in addition to ordering and comparing the differences, it is possible to relate in proportional terms the values ​​assumed by the different units. The ratio scale assumes an absolute zero that indicates the absolute absence of the phenomenon. The name ratio indicates that you can use the ratio of those variables to make a comparison. Thus, for example, a weight of 100 kg is twice the weight of 50 kg, which indicates that weight is a ratio variable.