Nominal factors like changes in the money supply only affect nominal variables like inflation.

For quantitative analysis, data is coded usually into measured and recorded as nominal or ordinal variables.

These variables could be dichotomous, ordinal or nominal variables.

Classic correspondence analysis is a statistical method that gives a score to every value of two nominal variables.

Cramér's V, a similar measure of association between nominal variables.

The AS curve is drawn given some nominal variable, such as the nominal wage rate.

According to the classical dichotomy theory, real variables and nominal variables are separate in the long-run, meaning they are not influenced by each other.

It is now possible to trace the influence of a change in a nominal monetary variable, the rate of interest, in this model.

The classical dichotomy is the assumption that there is a relatively clean distinction between overall increases or decreases in prices and underlying, "nominal" economic variables.

In statistics, Tschuprow's T is a measure of association between two nominal variables, giving a value between 0 and 1 (inclusive).