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I see what you're saying. I was pointing out the dangers of false negatives, but he responded that he hires 10% of the people he invites for an onsite intervie
by fsk 12y ago
I see what you're saying. I was pointing out the dangers of false negatives, but he responded that he hires 10% of the people he invites for an onsite interview.
Even if you hire 10% of the candidates you on-site interview, that says nothing about your actual false positive or false negative rate. For all I know, he could be weeding out all the top candidates at the pre-interivew stage, and then hiring the best of a mediocre group of people.
It's easy to measure your false positive rate, people you are forced to fire (or wish you could fire if not for corporate bureaucracy).
It's harder to measure your false negative rate. The only way you could measure your false negative rate is to pick a random sample of people who fail your interview, AND HIRE THEM ANYWAY. (However, that could be a lawsuit risk. It would be unfair to the people who hire despite failing the interview. A small business couldn't afford to do it, only some huge corporation could do the experiment.)
Also, I doubt the ability of most businesses to identify the best performers AFTER THEY ARE HIRED and working there for a couple of years.
- sytelus 12y agoNo, I did not say I hire 10% of candidates I interview :). What I said was that's a fair estimate in industry. I feel you are truly confused about FP and FN. Whether there are 99% bad developers out there or if you hire 10% of candidates you interview - these both quantities are independent of FN and FP. FN says that you are turning away X good people and it's again independent of FP which ultimately decides how many bad developers you would eventually end up hiring regardless of other 3 quantities I mentioned. See here: http://en.wikipedia.org/wiki/Confusion_matrix http://en.wikipedia.org/wiki/Confusion_matrix It's not easy to measure FN, FP, TN or TP. Even good people fail due to different reasons like bad manager and bad people may succeed despite of mediocre skills. Looking at who you had to fire or who got promoted doesn't give accurate measurements at all although they may serve as weak proxy. The scenario I described was hypothetical to point out that cost of FP is far more higher than additional cost in hiring due to FN.
- fsk 12y agoIf you increase FN and FP stays the same, you are more likely to make a bad hire. Do you understand this?
- sytelus 12y agoMay be I'm completely missing something here but my understanding is this: FP = (good hires you made) / (all hires you made). Your likelyhood of making bad hire is 1-FP. If you hired 100 people and your FP was 10% then on average you would have 10 bad hires on your team. So FP determines the number of bad hires you would eventually have. FN has nothing to do with it - it only determines how long before you make a good hire, it doesn't influence actual number of bad hires you will make. I'm using standard terminologies here. There are plenty of textbooks and articles on confusion matrix, precision, recall, RoC etc. Not sure what definitions you are using to arrive at conclusion that FN increases the number of good hires (it only increases effort).
- fsk 12y agoYou aren't using statisics correctly. FP = probability, given a bad candidate, you will hire him FN = probability, given a good candidate, you will pass Suppose 100 bad candidates, 10 good candidates FP=10%, FN=10% You make 10 bad hires and 9 good hires FP=10%, FN=20% You make 10 bad hires and 8 good hires. So increasing FN lowers your yield. Your statstic (good hires / total hires) tells you nothing about your actual FP or FN value. If you don't get it, I'm not wasting time on you anymore. You are very dangerous. You think you know statistics, but you don't.
- fsk 12y agoYour statistic (good hires / total hires), using the jargon from your link, is precision or positive predictive value (PPV). Using the math from that link, if you decrease FN, then PPV increases.
- deleted 12y ago[deleted]