Entering content frame

Object documentationR Square Locate the document in its SAP Library structure


In multiple linear regression, R square indicates how well a particular combination of X variables (the model drivers or independent variables) explains the variation in Y (the dependent variable).

R square ranges in value from 0 to 1. A value of 0 means that the multiple linear regression model does nothing to explain the variation in Y. A value of 1 means that the model is a perfect fit. A value of 0.9 or more indicates an acceptable model.

R square is also known as the coefficient of determination or measure of goodness-of-fit.

It is defined as

This graphic is explained in the accompanying text

where the total sum of squares is

This graphic is explained in the accompanying text


When comparing two models with this measure, make sure you use the same dependent variable.


R square is a nondescending function of the number of explanatory variables present in the model; that is, as you add more historical data and as you add more explanatory variables (X's), R square almost always increases and never decreases. This is because the addition of explanatory variables to the model causes prediction errors to be small.

Leaving content frame