Page 177 - Applied Statistics with R

9.5. SIMULATION 177

# SSE (For Full)
sum(resid(full_mpg_model) ^ 2)

## [1] 4530.466

# SST (For Null)
sum(resid(null_mpg_model) ^ 2)

## [1] 4556.646

# Degrees of Freedom: Diff
length(coef(full_mpg_model)) - length(coef(null_mpg_model))

## [1] 4

# Degrees of Freedom: Full
length(resid(full_mpg_model)) - length(coef(full_mpg_model))

## [1] 383

# Degrees of Freedom: Null
length(resid(null_mpg_model)) - length(coef(null_mpg_model))

## [1] 387

9.5 Simulation

Since we ignored the derivation of certain results, we will again use simulation to
convince ourselves of some of the above results. In particular, we will simulate
samples of size n = 100 from the model

= 5 + −2 + 6 + , = 1, 2, … ,

1

2
2
where ∼ (0, = 16). Here we have two predictors, so = 3.

set.seed(1337)
n = 100 # sample size
p = 3