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<html><head><title>R: Speed and Stopping Distances of Cars</title>
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<table width="100%" summary="page for cars"><tr><td>cars</td><td align="right">R Documentation</td></tr></table>

<h2>Speed and Stopping Distances of Cars</h2>

<h3>Description</h3>


<p>The data give the speed of cars and the distances taken to stop.
Note that the data were recorded in the 1920s.
</p>


<h3>Usage</h3>

<pre>cars</pre>


<h3>Format</h3>


<p>A data frame with 50 observations on 2 variables.
</p>

<table summary="Rd table">
<tr>
 <td align="right">
    [,1]  </td><td align="left"> speed  </td><td align="left"> numeric  </td><td align="left"> Speed (mph)</td>
</tr>
<tr>
 <td align="right">
    [,2]  </td><td align="left"> dist   </td><td align="left"> numeric  </td><td align="left"> Stopping distance (ft)
  </td>
</tr>

</table>



<h3>Source</h3>


<p>Ezekiel, M. (1930)
<EM>Methods of Correlation Analysis</EM>.
Wiley.
</p>


<h3>References</h3>


<p>McNeil, D. R. (1977)
<EM>Interactive Data Analysis</EM>.
Wiley.
</p>


<h3>Examples</h3>

<pre>
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 &lt;- lm(log(dist) ~ log(speed), data = cars))
opar &lt;- 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 &lt;- seq(0, 25, length.out = 200)
for(degree in 1:4) {
  fm &lt;- 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)
</pre>


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