Final answer:
The Residuals Versus Fitted Graph is a graphical representation of the residuals plotted against the predicted values from a regression analysis. It helps assess the goodness of fit of the regression line and identify potential outliers or influential points.
Step-by-step explanation:
The Residuals Versus Fitted Graph is a graphical representation of the residuals (or errors) plotted against the predicted values from a regression analysis. It helps us assess the goodness of fit of the regression line and identify potential outliers or influential points.
By plotting the residuals on the y-axis and the predicted values on the x-axis, we can visually examine the pattern of the residuals. If the residuals are randomly scattered around the horizontal line at zero, it indicates that the linear regression model is appropriate for the data.
However, if a clear pattern or systematic deviation is observed, it suggests that the linear regression model may not be suitable.
Additionally, the residuals versus fitted graph can help us identify outliers or influential points. These are data points that deviate significantly from the overall pattern of the data and can have a large impact on the regression line. Outliers may need to be investigated further to determine if they are valid data points or data entry errors.