This demo shows the possible QQ plots created by random numbers generated from a Normal distribution so that users can get a rough idea about how QQ plots really look like.
1  sim.qqnorm(n = 20, last.plot = NULL, ...)

n 
integer: sample size 
last.plot 
an expression to be evaluated after the plot is drawn, e.g.

... 
other arguments passed to 
When the sample size is small, it is hard to get a correct inference about the distribution of data from a QQ plot. Even if the sample size is large, usually there are outliers far away from the straight line. Therefore, don't overinterpret the QQ plots.
NULL
Yihui Xie
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18  oopt = ani.options(interval = 0.1, nmax = ifelse(interactive(), 100,
2))
par(mar = c(3, 3, 2, 0.5), mgp = c(1.5, 0.5, 0), tcl = 0.3)
sim.qqnorm(n = 20, last.plot = expression(abline(0, 1)))
## HTML animation pages
saveHTML({
par(mar = c(3, 3, 1, 0.5), mgp = c(1.5, 0.5, 0), tcl = 0.3)
ani.options(interval = 0.1, nmax = ifelse(interactive(), 100, 2))
sim.qqnorm(n = 15, pch = 20, main = "")
}, img.name = "sim.qqnorm", htmlfile = "sim.qqnorm.html", ani.height = 500,
ani.width = 500, title = "Demonstration of Simulated QQ Plots",
description = c("This animation shows the QQ plots of random numbers",
"from a Normal distribution. Does them really look like normally",
"distributed?"))
ani.options(oopt)

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