The

**adjusted R squared**is a modified version of R squared that has been adjusted for the number of predictors in a regression model. It is calculated as:**Adjusted R**= 1 – [ (1-R

^{2}^{2})(n-1) ] / (n-k-1)

where

*R*is the R squared of the model,^{2}*n*is the sample size, and*k*is the number of predictors in the model, not including the intercept.To calculate the adjusted R squared, simply fill in the values below and then click the “Calculate” button.

Adjusted R^{2} = **0.8551**

**Explanation:**

Adjusted R^{2} = 1 – [ (1-R^{2})(n-1) ] / (n-k-1)

Adjusted R^{2} = 1 = [ (1-0.87)(40-1) ] / (40–4-1)

Adjusted R^{2} = **0.8551**