Math for Finding a Wife
Funny analysis on optimizing how many women you should pass up before marrying. For those of you that don’t want to dig through the math, here is their summary for N=100 where N is the total number of single eligible women you can meet.
Thus the optimum strategy for N = 100 is to pass on the first 9 candidates and then select the next “best so far”. This gives an expected value of about 91.4, and the probability of selecting the very best candidate (“100”) with this strategy is 0.221. In contrast, if we used the strategy designed to optimize the probability of selecting the very best candidate, without regard to the value of any of the other candidates, we would pass on the first 100/e = 33 candidates. This gives a probability of 0.371 of selecting the very best candidate, but the expected value with this strategy is just 81.4.
Incidentally, it’s been called to my attention that the above formulas could, in certain circumstances, be used in a Bayesian way to estimate the number N of candidates that a man could have expected to encounter over his entire life, based on knowledge of having already met the very best woman. The “Amanda Rule” states that if a man knows, by some means, that the jth woman he has encountered is actually the very best, then a Bayesian estimate for the number N of women he would have expected to meet overall is roughly e times j. Of course, if he has already determined that the kth woman is the very best, he presumably has no interest in the remaining j(e-1) candidates, so the formula is of only academic interest.
