Hi
I am trying to simulate task estimation person days using this type of R
code. But I am not sure about reasoning here. Should the distribution be beta
or triangular or something else ? How do we get the values of mu,z and s here ?
Are there any explanations available ? Sections of some book ?
I have the book about monte carlo analysis using R but that looks like the next
step for me. I am at a preliminary stage.
taskestimation <- function( low , high, ci=0.9, n=10000) {
mu = mean(c(low,high))
z = qnorm(1-(1-ci)/2)
s = (high - mu)/z
rnorm(n, mu, s)
}
result = taskestimation(10,80)
#calculate the percentage of cases below certain number of days
length(result[result < 50])/length(result)
I am able to plot a density curve showing the percentage of completion below
'50' days that the simulation predicts.
Thanks,
Mohan
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