Standard deviation diagram, based an original graph by Jeremy Kemp, in 2005-02-09 [1]. This figure was started in R using:
# # 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))
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This chart was created with R.
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| act | 11:08 7 abr 2007 | 400×200 (14 KB) | Petter Strandmark | |
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