Here is a story about the woes of interpreting statistical distributions: I have two habits when I estimate: First, I like to give a range or even better a tri

Here is a story about the woes of interpreting statistical distributions: I have two habits when I estimate: First, I like to give a range or even better a triple estimate of "optimistic", "expected", "worst case". (And btw, you should expect things to weight toward the pessimistic side, because you always find new requirements/problems, but you rarely discover a supposed requirement is not really one.) Second: I like to break down a project into tasks of just a few hours and then add everything up. I usually don't share that spreadsheet with the customer, but it helps me a lot. Pretty much always it gives me a number higher than I'd like, but which is almost always very accurate. A couple times I've ignored the result and given a lower estimate because I really wanted some project, and it has always turned out the spreadsheet was right. Well, one time I combined these two approaches, so that my very finely-chopped estimates all had best/expected/worst values, and I shared that with the customer. Of course they took one look at the worst-case total and said, "How can a little thing like this possibly take 2 years??" I didn't get the work. :-) EDIT: Btw it feels like there is a "coastline paradox" here, where the more finely you estimate, the higher the max possible, so that you can make your estimate grow without bound as long as you keep splitting items into greater detail. It'd be interesting to see the math for that.