R-Squared

An R-squared value is the proportion of total variability in the data which is explained by the regression model. It is computed as the regression or model Sum of Squares (SS) divided by the total sum of squares.

Values: Range is 0 to 1.

Troubleshooting: An R-squared of 1 indicates a perfect model. This is unlikely and may be due to the number of terms being the same as the number of data points. Check the number of Error Degrees of Freedom in the fit for regression response summary area. Generally, the more Error Degrees of Freedom a model has, the better you can quantify the fit. You should add a few extra runs and then fit the model. An R-squared of 0 indicates that the data is purely random or that the model is totally inappropriate. You should check the range of response values to make sure that they make physical sense. Ideally, you should obtain R-squared values greater than 0.9 for high confidence in the results.