Overlay normal curve to histogram in R

Question

I have managed to find online how to overlay a normal curve to a histogram in R, but I would like to retain the normal "frequency" y-axis of a histogram. See two code segments below, and notice how in the second, the y-axis is replaced with "density". How can I keep that y-axis as "frequency", as it is in the first plot.

AS A BONUS: I'd like to mark the SD regions (up to 3 SD) on the density curve as well. How can I do this? I tried abline, but the line extends to the top of the graph and looks ugly.

g = d$mydata hist(g) 

g = d$mydata m<-mean(g) std<-sqrt(var(g)) hist(g, density=20, breaks=20, prob=TRUE,       xlab="x-variable", ylim=c(0, 2),       main="normal curve over histogram") curve(dnorm(x, mean=m, sd=std),        col="darkblue", lwd=2, add=TRUE, yaxt="n") 

See how in the image above, the y-axis is "density". I'd like to get that to be "frequency".

Answer 1

Here's a nice easy way I found:

h <- hist(g, breaks = 10, density = 10,           col = "lightgray", xlab = "Accuracy", main = "Overall")  xfit <- seq(min(g), max(g), length = 40)  yfit <- dnorm(xfit, mean = mean(g), sd = sd(g))  yfit <- yfit * diff(h$mids[1:2]) * length(g)   lines(xfit, yfit, col = "black", lwd = 2) 

Answer 2

You need to find the right multiplier to convert density (an estimated curve where the area beneath the curve is 1) to counts. This can be easily calculated from the hist object.

myhist <- hist(mtcars$mpg) multiplier <- myhist$counts / myhist$density mydensity <- density(mtcars$mpg) mydensity$y <- mydensity$y * multiplier[1]  plot(myhist) lines(mydensity) 

A more complete version, with a normal density and lines at each standard deviation away from the mean (including the mean):

myhist <- hist(mtcars$mpg) multiplier <- myhist$counts / myhist$density mydensity <- density(mtcars$mpg) mydensity$y <- mydensity$y * multiplier[1]  plot(myhist) lines(mydensity)  myx <- seq(min(mtcars$mpg), max(mtcars$mpg), length.out= 100) mymean <- mean(mtcars$mpg) mysd <- sd(mtcars$mpg)  normal <- dnorm(x = myx, mean = mymean, sd = mysd) lines(myx, normal * multiplier[1], col = "blue", lwd = 2)  sd_x <- seq(mymean - 3 * mysd, mymean + 3 * mysd, by = mysd) sd_y <- dnorm(x = sd_x, mean = mymean, sd = mysd) * multiplier[1]  segments(x0 = sd_x, y0= 0, x1 = sd_x, y1 = sd_y, col = "firebrick4", lwd = 2)