cars: cars

Description

A data frame with 54 rows and 6 columns. The columns represent the variables type, price, mpgCity, driveTrain, passengers, weight for a sample of 54 cars from 1993. This data is a subset of the Cars93 data set from the MASS package.

Usage

data(cars)

Arguments

Format

A data frame with 54 observations on the following 6 variables.

type: The vehicle type with levels large, midsize, and small.
price: Vehicle price (USD).
mpgCity: Vehicle mileage in city (miles per gallon).
driveTrain: Vehicle drive train with levels 4WD, front, and rear.
passengers: The vehicle passenger capacity.
weight: Vehicle weight (lbs).

Details

These cars represent a random sample for 1993 models that were in both Consumer Reports and PACE Buying Guide. Only vehicles of type 'small', 'midsize', and 'large' were include.

Further description can be found in Lock (1993). Use the URL http://www.amstat.org/publications/jse/v1n1/datasets.lock.html.

References

http://www.openintro.org/

Examples

Run this code

# NOT RUN {
data(cars)

#===> vehicle price by type <===#
par(mfrow=c(1,1))
histPlot(cars$price[cars$type=='small'], probability=TRUE,
	hollow=TRUE, xlim=c(0,50))
histPlot(cars$price[cars$type=='midsize'], probability=TRUE,
	hollow=TRUE, add=TRUE, border='red', lty=3)
histPlot(cars$price[cars$type=='large'], probability=TRUE,
	hollow=TRUE, add=TRUE, border='blue', lty=4)
legend('topright', lty=2:4, col=c('black', 'red', 'blue'),
	legend=c('small', 'midsize', 'large'))

#===> vehicle price versus weight <===#
plot(cars$weight, cars$price, col=fadeColor('magenta', '88'),
	pch=20, cex=2)

#===> mileage versus weight <===#
plot(cars$weight, cars$mpgCity, type="n")
temp <- c(seq(1000, 5000, 100), rev(seq(1000, 5000, 100)), 1000)
hold <- 87.11 - 0.03508*temp + 0.000004432*temp^2 + 7*c(rep(-1, 41), rep(1, 41), 1)
polygon(temp, hold, col="#E2E2E2",
	border=fadeColor('black', '00'))
points(cars$weight, cars$mpgCity,
	col='chocolate4', pch=20, cex=2)
# }

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