For example, in R if you call the
acf() function it plots a correlogram by default, and draws a 95% confidence interval. Looking at the code, if you call
plot(acf_object, ci.type="white"), you see:
qnorm((1 + ci)/2)/sqrt(x$n.used)
as upper limit for type white-noise. Can some one explain theory behind this method? Why do we get the qnorm of 1+0.95 and then divide by 2 and after that, divide by the number of observations?