why do residuals plot for linear models why do residuals and fitted values differ in r plots? why are residuals versus fitted values plots justified why does the third plot mean a nonlinear model why the plot of residuals and the fitted value is different in a linear model? why would two plots indicate a heteroscedastic model which plot of a linear model indicates that residuals are normally distributed? which is true of residual models in r? why does plot 3 indicate linear model why is the plot between the residuals and the fitting values strongly nonlinear? why does the third plot suggest a nonlinear model why are the residuals and a linear model correlated in a second plot? why is the second plot correlated with the fitted values of a linear model? what do the residuals of a linear model mean what is the residual plot in regression difference between a second plot of data and the third plot of data what does the third plot in faraway's linear model mean? why do the plots indicate a heteroscedastic linear model which of the following indicates non-linearity, but a regression model? why is a third plot necessary when performing a normalized linear model?