Page 347 - Applied Statistics with R

14.2. PREDICTOR TRANSFORMATION 347

Simulated Quadratic Data

120

80
y 60

40
20

0

0 1 2 3 4 5

x

par(mfrow = c(1, 2))

plot(fitted(lin_fit), resid(lin_fit), col = "grey", pch = 20,
xlab = "Fitted", ylab = "Residuals", main = "Fitted versus Residuals")
abline(h = 0, col = "darkorange", lwd = 2)

qqnorm(resid(lin_fit), main = "Normal Q-Q Plot", col = "darkgrey")
qqline(resid(lin_fit), col = "dodgerblue", lwd = 2)

Fitted versus Residuals Normal Q-Q Plot

20 20
10 10
Residuals 0 Sample Quantiles 0

-10 -10
-20 -20

-20 0 20 40 60 80 100 -3 -2 -1 0 1 2 3
Fitted Theoretical Quantiles