Adding Measures of Central Tendency to Histograms in R

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Building on the basic histogram with a density plot, we can add measures of central tendency (in this case, mean and median) and a legend.

Like last time, we’ll use the beaver data from the datasets package.

hist(beaver1$temp, # histogram
 col = "peachpuff", # column color
 border = "black", 
 prob = TRUE, # show densities instead of frequencies
 xlim = c(36,38.5),
 ylim = c(0,3),
 xlab = "Temperature",
 main = "Beaver #1")
lines(density(beaver1$temp), # density plot
 lwd = 2, # thickness of line
 col = "chocolate3")

Next we’ll add a line for the mean:

abline(v = mean(beaver1$temp),
 col = "royalblue",
 lwd = 2)

And a line for the median:
abline(v = median(beaver1$temp),
 col = "red",
 lwd = 2)

And then we can also add a legend, so it will be easy to tell which line is which.
legend(x = "topright", # location of legend within plot area
 c("Density plot", "Mean", "Median"),
 col = c("chocolate3", "royalblue", "red"),
 lwd = c(2, 2, 2))

All of this together gives us the following graphic:

In this example, the mean and median are very close, as we can see by using median() and mode().
> mean(beaver1$temp)
[1] 36.86219

> median(beaver1$temp)
[1] 36.87

We can do like we did in the previous post and graph beaver1 and beaver2 together by adding a layout line and changing the limits of x and y. The full code for this is available in a gist.

Here’s the output from that code:

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