Ask HN: What's your speciality, and what's your "FizzBuzz" equivalent?

1) That the proposer of the question often understands the job. (by which i mean, in real world interviews. I'm not commenting on the specific poster).

2) I am not saying that I couldn't do the question, per se.

On the contrary, my professional work shows not only that I can do the question, but that I've probably done it innumerable times and to the standard of (and sometimes greater than) other professionals.

The subtext of my response to the bond question shows that, in an absolute juvenile sense, I "know" the answer that's being looked for because I've notionally been trained as en economist. Which is to say, I am aware of the rote learned current models/theory.

I'm saying that I probably couldn't answer it in the interview environment in the way that most interviewers would deem "acceptable" or "right".

Why? Because I both haven't memorized Bayes theorem, and wouldn't accept there as being a simple probabilistic interpretation applicable to real world problems. Now its true, I could probably attempt to re-derive it there in the interview from some even more basic understandings of probability, but is that what interviewers want? I'd almost certainly offer the answer of "Can i look at the two sides of the coin?" or "the probability is either 0 or 1". And then we'd go down the path of probability interpretations, and then only after they made it clear that they wanted a Bayesian approach, we could start heading in that direction. Is that what they're looking for? I don't think it is. But they are all valid responses.

I think they want someone who has remembered Bayes and its application recently and then just applied it. I think in the bond question, they want someone who has rote learnt some economic/finance theory. And I think the worst aspect is that the stronger candidate, who pauses, who thinks, who questions, and who doesn't just go down the regurgitated answer will probably, in real life, be marked as the weaker candidate.

And I'm also saying this as someone who is already employed, being paid and and working professionally on things the questions are supposed to be screening for. So while the original poster is in a position of authority to speak of such things, so am I.

Are you familiar with Project Euler? I've completed many of those problems as well, but I would never expect myself or some other candidate to be able to do them spontaneously in said interview, or think worse of them if they couldn't. And if they could do them, I don't think that would be an indicator of very much more than the fact that they happened to be working on said problem recently, had just taken a course on said problem, or had just been doing interview questions for my field.

I am genuinely skeptical about whether people who don't know what they're talking about can actually hide that fact from people who do know what they're talking about in such a situation. The secret of course is to basically ignore qualifications/status and do it as a conversation. Perhaps in such a scenario, five minutes in me and the original poster would be getting onto ridiculous questions of trading/probability with great big smiles on our faces and forgetting all about whether one can remember bayes off the top of their head.

The second part: Assessing the technical ability of the candidate at hand. And for this I think current interview culture is horribly toxic.

I do not work for Facebook, nor do I believe that such techniques are not without their flaws, and are difficult/expensive to implement, but I think techniques aimed at "actually get the candidate to do the task involved in the job, and see how they go" has merit. Forget your preconceptions about what is required. Give them a real world task you'd expect them to do in the job, the time it would be expected of someone in the job. The resources of the job. See how they go.: See http://www.kaggle.com/c/facebook-recruiting-iii-keyword-extr... for example.

Not perfect, but better than 5 minute "interviewer questions of the year".

Funnily enough, I got into my current organisation answering questions in the interview on analyzing health statistics. Something I knew nothing about. A senior executive then snatched/let me move across to his area in the more technical side of things without a subsequent interview after I made it known I'd be interested, and after working with their guys for a bit on another project. Swings and roundabouts :P

That's not the reason. It's because the fake coin also has two sides and therefore also 2^11 different outcomes. It just happens they all look the same.

Otherwise I agree with your argument.

I like a "factor label" style approach where you can see the prior probability (Fair: Biased), the information about the flips, and the posterior probability (the revised chances after the new information is taken into account):

Prior * Information = Posterior

so

(Fair : Biased) * (10 Fair heads : Fair ) : (10 Biased heads : Biased) = 10 Fair Heads : 10 Biased Heads

Plugging in, we'd have:

(999 / 1) * (1 / 1024 ) / (1 / 1) = 999 / 1024

The odds are ever-slightly in favor of a biased coin. So we can mentally guess ever-slightly above 3/4 for the chance of another heads. We could write (999/2 + 1024) / (999 + 1024) on the whiteboard to be exact.