The adjective simple refers to the fact that the outcome variable is related to a single predictor. That is, it concerns two-dimensional sample points with one independent variable and one dependent variable (conventionally, the x and y coordinates in a Cartesian coordinate system) and finds a linear function (a non-vertical straight line) that, as accurately as possible, predicts the dependent variable values as a function of the independent variable. In statistics, simple linear regression is a linear regression model with a single explanatory variable. Here the dependent variable (GDP growth) is presumed to be in a linear relationship with the changes in the unemployment rate. Okun's law in macroeconomics is an example of the simple linear regression.
Linear regression model with a single explanatory variable Part of a series on
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