This graph shows the observed response variable vs the predicted response variable (for a particular model). What is the correct interpretation? Observed vs. predicted 120000- 90000- 60000- Observed response variable (y) 30000- 0- 0 25000 50000 75000 100000 Predicted response variable The model violates the assumption of linearity The model violates the assumption of constant variation of the residuals The model violates the assumption of nearly normal residuals None of the assumptions of the linear model appear to be violated.
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Suppose we have a plot of the residuals versus the fitted values. Which of the following would indicate a nonlinear relationship between the predictors and the response? The spread in the residuals increases with the predicted values. A linear pattern in the residual plot. No pattern in the residual plot. The spread in the residuals decreases with the predicted values.
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