carprice: US Car Price Data

Description

U.S. data extracted from Cars93, a data frame in the MASS package.

Usage

carprice

Arguments

Format

This data frame contains the following columns:

Type: Type of car, e.g. Sporty, Van, Compact
Min.Price: Price for a basic model
Price: Price for a mid-range model
Max.Price: Price for a `premium' model
Range.Price: Difference between Max.Price and Min.Price
RoughRange: Rough.Range plus some N(0,.0001) noise
gpm100: The number of gallons required to travel 100 miles
MPG.city: Average number of miles per gallon for city driving
MPG.highway: Average number of miles per gallon for highway driving

References

Venables, W.N.\ and Ripley, B.D., 4th edn 2002. Modern Applied Statistics with S. Springer, New York.

See also `R' Complements to Modern Applied Statistics with S-Plus, available from http://www.stats.ox.ac.uk/pub/MASS3/

Examples

Run this code

print("Multicollinearity - Example 6.8")
pairs(carprice[,-c(1,8,9)])

carprice1.lm <- lm(gpm100 ~ Type+Min.Price+Price+Max.Price+Range.Price,
    data=carprice)
round(summary(carprice1.lm)$coef,3)
pause()

alias(carprice1.lm)
pause()

carprice2.lm <- lm(gpm100 ~ Type+Min.Price+Price+Max.Price+RoughRange, data=carprice)
round(summary(carprice2.lm)$coef, 2)
pause()

carprice.lm <- lm(gpm100 ~ Type + Price, data = carprice)
round(summary(carprice.lm)$coef,4)  
pause()

summary(carprice1.lm)$sigma   # residual standard error when fitting all 3 price variables
pause()

summary(carprice.lm)$sigma    # residual standard error when only price is used
pause()

vif(lm(gpm100 ~ Price, data=carprice)) # Baseline Price
pause()

vif(carprice1.lm)    # includes Min.Price, Price & Max.Price
pause()

vif(carprice2.lm)    # includes Min.Price, Price, Max.Price & RoughRange
pause()

vif(carprice.lm)     # Price alone

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