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Purple Question



For this problem, we’ll use the mtcars data. Use the first 20 rows of mtcars to estimate the following regression

\[ mpg = \beta_0 + \beta_1 hp + \beta_2 wt + \beta_3 gear + U \]

Using these regression results, predict mpg for the remaining 12 observations in mtcars. Which of these cars has the largest prediction error in absolute value?

Rules:

To win

Raise your hand, and tell me which car has the largest prediction error in absolute value, and your team will advance to the championship code challenge.



Solution below…















train_data <- mtcars[1:20,]
test_data <- mtcars[21:(nrow(mtcars)), ]

train_reg <- lm(mpg ~ hp + wt + gear, data=mtcars)

Yhat <- predict(train_reg, newdata=test_data)

uhat <- test_data$mpg - Yhat

uhat
##    Toyota Corona Dodge Challenger      AMC Javelin       Camaro Z28 
##       -2.1227485       -2.7993972       -3.3712111       -0.4814222 
## Pontiac Firebird        Fiat X1-9    Porsche 914-2     Lotus Europa 
##        2.8595428       -0.1779368       -0.9227150        2.2815510 
##   Ford Pantera L     Ferrari Dino    Maserati Bora       Volvo 142E 
##       -1.4649819       -2.1180654        1.6259525       -1.7939863
max(abs(uhat))
## [1] 3.371211

which is the prediction error for the AMC Javelin