Histogramms are commonly used in data analysis to observe distribution of variables.

Really often we need to compare the distribution of 2 variables simultaneously.

There is a tip to present the 2 distribution together (using the add function) with transparency (using the rgb function) to keep information when data override.

#Create data
Ixos=rnorm(4000 , 100 , 30)     
Primadur=rnorm(4000 , 200 , 30) 

#Represent separately first
par(mfrow=c(1,2))
hist(Ixos, breaks=30 , xlim=c(0,300) , col=rgb(1,0,0,0.5) , xlab="height" , ylab="nbr of plants" , main="" )
hist(Primadur, breaks=30 , xlim=c(0,300) , col=rgb(0,0,1,0.5) , xlab="height" , ylab="nbr of plants" , main="")

#But it is hard to visualize differences in the distribution. 
#It would be more interesting to have both distribution on the same graph, 
#with transparency permitting to see the whole distribution :
hist(Ixos, breaks=30, xlim=c(0,300), col=rgb(1,0,0,0.5), xlab="height", 
     ylab="nbr of plants", main="distribution of height of 2 durum wheat varieties" )
hist(Primadur, breaks=30, xlim=c(0,300), col=rgb(0,0,1,0.5), add=T)
legend("topright", legend=c("Ixos","Primadur"), col=c(rgb(1,0,0,0.5), 
     rgb(0,0,1,0.5)), pt.cex=2, pch=15 )