Secretary Problem

This can be made much more efficient if you just take all of the applications and throw half of them away.<p>This will ensure that all the remaining applicants are luckier than the average applicant.

This problem is the underpinning of lots of real-life problems. Basically any search where revisiting a previously evaluated choice is expensive.

I learned about this in the book Algorithms to Live By. They talk about it in the context of dating; How do you know if you&#x27;ve met the right one? IIRC you have to go on x amount of dates knowing you won&#x27;t commit to this person.<p>The book has an interesting way of looking at life, recommend.

&gt;&gt; is simple and selects the single best candidate about 37% of the time<p>Not a mathematician but 1 &#x2F; e = 0.367, so is this just a way to ensure a 37% percentile of accuracy across normal distribution? Like Anchorman Sex Panther, &quot;37% of the time it works every time&quot;?

I wonder what happens when there&#x27;s lots of noise in the estimation of quality or fit (or whatever underlies the preference ranking). I imagine this has been done?

&gt; The applicants, if all seen together, can be ranked from best to worst unambiguously.<p>Sounds to me like the actual objective is to hire the hottest-looking secretary.