cars
Speed and Stopping Distances of Cars
The data give the speed of cars and the distances taken to stop. Note that the data were recorded in the 1920s.
Usage
cars
Format
A data frame with 50 observations on 2 variables.
| [,1] | speed | numeric | Speed (mph) |
| [,2] | dist | numeric | Stopping distance (ft) |
Source
Ezekiel, M. (1930) Methods of Correlation Analysis. Wiley.
References
McNeil, D. R. (1977) Interactive Data Analysis. Wiley.
Examples
require(stats); require(graphics)
plot(cars, xlab = "Speed (mph)", ylab = "Stopping distance (ft)",
las = 1)
lines(lowess(cars$speed, cars$dist, f = 2/3, iter = 3), col = "red")
title(main = "cars data")
plot(cars, xlab = "Speed (mph)", ylab = "Stopping distance (ft)",
las = 1, log = "xy")
title(main = "cars data (logarithmic scales)")
lines(lowess(cars$speed, cars$dist, f = 2/3, iter = 3), col = "red")
summary(fm1 <- lm(log(dist) ~ log(speed), data = cars))
opar <- par(mfrow = c(2, 2), oma = c(0, 0, 1.1, 0),
mar = c(4.1, 4.1, 2.1, 1.1))
plot(fm1)
par(opar)
## An example of polynomial regression
plot(cars, xlab = "Speed (mph)", ylab = "Stopping distance (ft)",
las = 1, xlim = c(0, 25))
d <- seq(0, 25, length.out = 200)
for(degree in 1:4) {
fm <- lm(dist ~ poly(speed, degree), data = cars)
assign(paste("cars", degree, sep = "."), fm)
lines(d, predict(fm, data.frame(speed = d)), col = degree)
}
anova(cars.1, cars.2, cars.3, cars.4)
<iframe src="https://pmagunia.com/iframe/cars.html" width="100%" height="100%" style="border:0px"></iframe>