Plots of Observed Responses Versus Fitted Responses for Two Regression Models
Fitted responses
Observed responses
Observed responses
Percentage of response variable variation that is explained by its relationship with one or more predictor variables. In general, the higher the R2 , the better the model fits your data. R2 is always between 0 and 100%. It is also known as the coefficient of determination or multiple determination (in multiple regression).
Plotting observed values by fitted values graphically illustrates R2 values for regression models.
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Plots of Observed Responses Versus Fitted Responses for Two Regression Models |
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Fitted responses |
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Observed responses |
Observed responses |
The regression model on the left accounts for 38.0% of the variance while the one on the right accounts for 87.4%. The more variance that is accounted for by the regression model the closer the data points will fall to the fitted regression line. Theoretically, if a model could explain 100% of the variance, the fitted values would always equal the observed values and, therefore, all the data points would fall on the fitted regression line.