Page 345 - Applied Statistics with R

14.2. PREDICTOR TRANSFORMATION 345

Fitted versus Residuals Normal Q-Q Plot
0.4 0.4

0.2 0.2
Residuals 0.0 -0.2 Sample Quantiles 0.0 -0.2

-0.4 -0.4

-0.6 -0.6
10.5 11.0 11.5 12.0 12.5 -2 -1 0 1 2
Fitted Theoretical Quantiles

sqrt(mean(resid(initech_fit) ^ 2))

## [1] 27080.16

sqrt(mean(resid(initech_fit_log) ^ 2))

## [1] 0.1934907

sqrt(mean((initech$salary - fitted(initech_fit)) ^ 2))

## [1] 27080.16

sqrt(mean((initech$salary - exp(fitted(initech_fit_log))) ^ 2))

## [1] 24280.36

Predictor Transformations

14.2.2 A Quadratic Model

sim_quad = function(sample_size = 500) {
x = runif(n = sample_size) * 5
y = 3 + 5 * x ^ 2 + rnorm(n = sample_size, mean = 0, sd = 5)
data.frame(x, y)
}