I decided this seems like something one should be able to calculate with conditional probability. Let P(A) be the probability that someone is a pretty good pro

I decided this seems like something one should be able to calculate with conditional probability. Let P(A) be the probability that someone is a pretty good programmer. (I said top ten percent, so .1). P(A') is 1-P(A) = .9 Let P(E) be the probability someone is employed. I guessed and put that at 1-P(E'), guessing programmer unemployment rate at 6%. P(E) = .94 P(E') = .06 Here is a more wild assumption. Let's say that given that someone is a top 10% programmer, there is a 98% probability that he or she is employed. P(E | A) = .98, and conversely, a .02 probability they aren not. With these assumptions in place, I ran the calculations. I was intending to type them up, but it would be difficult with just a text area. Here is the punch line (with those symbols, and assuming I did this correctly, which I did it on the bus on the way home, so probably not)... Given that someone is unemployed, there is a .033 probability that they are in the top 10% and a .96 probability that they are somewhere among the rest. (The 'rest' includes a lot of pretty decent programmers though!) In other words, 3.3% of applicants would be top 10% candidates, and that's assuming equal probability of them sending in an application in the first place. I might rework it with different assumptions. Anyway, you said the math was pretty simple. If someone wants to see how I screwed it up I can type it up into latex and upload it somewhere.