Model Summary

The model summary table reports the strength of the relationship between the model and the dependent variable. R, the multiple correlation coefficient, is the linear correlation between the observed and model-predicted values of the dependent variable. Its large value indicates a strong relationship.

R Square, the coefficient of determination, is the squared value of the multiple correlation coefficient. It shows that 78.3% of the variation in time is explained by the model.

Adjusted R Square is a "corrected" R Square statistic that penalizes models with large numbers of parameters.

These statistics, along with the standard error of the estimate, are most useful as comparative measures to choose between two or more models.

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