Not Just Normal… Gaussian

June 16, 2009
By

[This article was first published on Cerebral Mastication » R, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Pretty Normal

Pretty Normal

Dave, over at The Revolutions Blog, posted about the big ‘ol list of graphs created with R that are over at Wikimedia Commons. As I was scrolling through the list I recognized the standard normal distribution from the Wikipedia article on the same topic.

Below is the fairly simple source code with lots of comments. Here’s the source. Run it at home… for fun and profit.

# # External package to generate four shades of blue
# library(RColorBrewer)
# cols <- rev(brewer.pal(4, "Blues"))
cols <- c("#2171B5", "#6BAED6", "#BDD7E7", "#EFF3FF")

# Sequence between -4 and 4 with 0.1 steps
x <- seq(-4, 4, 0.1)

# Plot an empty chart with tight axis boundaries, and axis lines on bottom and left
plot(x, type="n", xaxs="i", yaxs="i", xlim=c(-4, 4), ylim=c(0, 0.4),
     bty="l", xaxt="n", xlab="x-value", ylab="probability density")

# Function to plot each coloured portion of the curve, between "a" and "b" as a
# polygon; the function "dnorm" is the normal probability density function
polysection <- function(a, b, col, n=11){
    dx <- seq(a, b, length.out=n)
    polygon(c(a, dx, b), c(0, dnorm(dx), 0), col=col, border=NA)
    # draw a white vertical line on "inside" side to separate each section
    segments(a, 0, a, dnorm(a), col="white")
}

# Build the four left and right portions of this bell curve
for(i in 0:3){
    polysection(   i, i+1,  col=cols[i+1]) # Right side of 0
    polysection(-i-1,  -i,  col=cols[i+1]) # Left right of 0
}

# Black outline of bell curve
lines(x, dnorm(x))

# Bottom axis values, where sigma represents standard deviation and mu is the mean
axis(1, at=-3:3, labels=expression(-3*sigma, -2*sigma, -1*sigma, mu,
                                    1*sigma,  2*sigma,  3*sigma))

# Add percent densities to each division, between x and x+1
pd <- sprintf("%.1f%%", 100*(pnorm(1:4) - pnorm(0:3)))
text(c((0:3)+0.5,(0:-3)-0.5), c(0.16, 0.05, 0.04, 0.02), pd, col=c("white","white","black","black"))
segments(c(-2.5, -3.5, 2.5, 3.5), dnorm(c(2.5, 3.5)), c(-2.5, -3.5, 2.5, 3.5), c(0.03, 0.01))

To leave a comment for the author, please follow the link and comment on their blog: Cerebral Mastication » R.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.



If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Tags: , ,

Comments are closed.

Search R-bloggers

Sponsors

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)