Histograms

Sameer Mathur

Simple Histograms

hist(mtcars$mpg)

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Histogram with Specified Number of Bins

hist(mtcars$mpg, 
     breaks=12, 
     xlab="Miles Per Gallon", 
     main="Histogram with specified number of bins")

Histogram with 12 Number of Bins

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Kernel Density Curve

p <- plot(density(mtcars$mpg))
lines(p, col="black", lwd=2)

We can see the distribution of continuous variable using the kernel density plots.

Kernel Density Curve

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Histogram with Density Curve

hist(mtcars$mpg, 
     freq=FALSE, 
     breaks=12, 
     xlab="Miles Per Gallon", 
     main="Histogram with density curve")  
lines(density(mtcars$mpg), col="black", lwd=2)

Histogram with Density Curve

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Histogram with Rug Plot

hist(mtcars$mpg, 
     freq=FALSE, 
     breaks=12, 
     xlab="Miles Per Gallon", 
     main="Histogram with rug plot")  
rug(jitter(mtcars$mpg))

A rug plot is one dimensional representation of the actual data values. If there are many tied values, we can jitter the data on the rug plot.

Histogram with Rug Plot

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