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If you choose your employees at random from the pool of applicants, and the applicants' abilities are normally distributed, then you're right that the employees

by jleader 13y ago

If you choose your employees at random from the pool of applicants, and the applicants' abilities are normally distributed, then you're right that the employees' performance will be normally distributed. But I would expect any tech firm's hiring criteria to have at least some correlation with employees' performance, which means their performance will be biased towards the high end of the curve. So no, the skill of the engineers probably shouldn't follow a normal distribution.

tiziano88 13y ago
By definition, average is in the middle of whatever distribution they follow. Maybe median would be a more appropriate point to measure against though.
- lutusp 13y ago
  > By definition, average is in the middle of whatever distribution they follow. Not necessarily the middle. In a skewed distribution, the average is still the sum of the samples divided by the number of samples, but it's not located at the middle (centerpoint) of the sample set. > Maybe median would be a more appropriate point to measure against though. You managed to get that exactly backwards. It's the median that's located at the middle of the distribution, not the mean. For a balanced distribution, they're the same, but for a skewed distribution, it's the mean that moves away from the "middle", not the median.
craigyk 13y ago
I think you are wrong. I think randomly drawing any significant number of people from a pool that isn't normally distributed is still likely to result in a normal distribution. http://en.wikipedia.org/wiki/Central_limit_theorem http://en.wikipedia.org/wiki/Central_limit_theorem
- zosima 13y ago
  No, that's not quite right. Randomly picking people from a distribution should eventually end up giving the original distribution. Taking n people from a pool m times, then the means of those m samplings will be normally distributed however (given the constraints of the CLT of course).

by jleader 13y ago

tiziano88 13y ago

By definition, average is in the middle of whatever distribution they follow. Maybe median would be a more appropriate point to measure against though.

lutusp 13y ago
> By definition, average is in the middle of whatever distribution they follow. Not necessarily the middle. In a skewed distribution, the average is still the sum of the samples divided by the number of samples, but it's not located at the middle (centerpoint) of the sample set. > Maybe median would be a more appropriate point to measure against though. You managed to get that exactly backwards. It's the median that's located at the middle of the distribution, not the mean. For a balanced distribution, they're the same, but for a skewed distribution, it's the mean that moves away from the "middle", not the median.

craigyk 13y ago

I think you are wrong. I think randomly drawing any significant number of people from a pool that isn't normally distributed is still likely to result in a normal distribution. http://en.wikipedia.org/wiki/Central_limit_theorem http://en.wikipedia.org/wiki/Central_limit_theorem

zosima 13y ago
No, that's not quite right. Randomly picking people from a distribution should eventually end up giving the original distribution. Taking n people from a pool m times, then the means of those m samplings will be normally distributed however (given the constraints of the CLT of course).