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Lots of math in here premised on shaky foundations: >Group A comes from a population where the chance of graduation is distributed uniformly from 0% to 100% an

Lots of math in here premised on shaky foundations: >Group A comes from a population where the chance of graduation is distributed uniformly from 0% to 100% and group B is from one where the chance is distributed uniformly from 10% to 90% >The mean of group B is not lower because of bias (which would be reflected near x=80), but because the very best members of group B are simply not as good as the very best members of group A. Yes, if we can assume some a-priori knowledge about certain "groups" of people, then we can make a more "informed" decision. That's pretty much the definition of bias, isn't it? Paul Graham's point, as I understood it, was that those assumptions are often invalid. Therefore, bias could cause the market to under value someone or some company. Your counterpoint seems to be, "let's suppose those biases are legitimate."

nshepperd 11y ago
Read it again. He's talking about the counterexample there. It's a hypothetical.
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- LordHumungous 11y ago
  Yes I get that. The crux of his argument is: >Unfortunately, using the mean as a test statistic is flawed - it only works when the pre-selection distribution of A and B is identical, at least beyond C His argument is based the proposition that different sexes/races have different market value profiles. He needs to demonstrate why that is the case before proceeding to heavy math.
  - nshepperd 11y ago
    No, he's not asserting any such thing. Again, it's a hypothetical. A counterexample that means, yes, the "mean" test is flawed. Because it doesn't work in all scenarios.
  - zodiac 11y ago
    > His argument is based the proposition that different sexes/races have different market value profiles. He needs to demonstrate why that is the case before proceeding to heavy math. Not really, his argument is that "PG's mean-post selection test (the 'PMST') is only valid if different sexes have the same distribution of abilities". If you or PG believe that the PMST is a valid way of showing that bias exists, the burden is on you to show that different sexes have the same distribution of abilities.
    - LordHumungous 11y ago
      From the Paul Graham article: >You can use this technique whenever (a) you have at least a random sample of the applicants that were selected, (b) their subsequent performance is measured, and (c) the groups of applicants you're comparing have roughly equal distribution of ability. So yes, OP is ignoring the entire premise of PG's argument.
      - zodiac 11y ago
        OP acknowledges this... "Unfortunately, using the mean as a test statistic is flawed - it only works when the pre-selection distribution of A and B is identical, at least beyond C." To me the rest of the article is asks the question, "requirement (c) is really strong, is there a way we can use post-selection statistics to determine bias while weakening (c)? what if we tried measuring the post-selection minimum instead of the mean?" Also PG edited his essay to add that disclaimer only after WildUtah's comment, so it's possible that OP hasn't read the updated version.

nshepperd 11y ago

Read it again. He's talking about the counterexample there. It's a hypothetical.

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LordHumungous 11y ago
Yes I get that. The crux of his argument is: >Unfortunately, using the mean as a test statistic is flawed - it only works when the pre-selection distribution of A and B is identical, at least beyond C His argument is based the proposition that different sexes/races have different market value profiles. He needs to demonstrate why that is the case before proceeding to heavy math.
- nshepperd 11y ago
  No, he's not asserting any such thing. Again, it's a hypothetical. A counterexample that means, yes, the "mean" test is flawed. Because it doesn't work in all scenarios.
- zodiac 11y ago
  > His argument is based the proposition that different sexes/races have different market value profiles. He needs to demonstrate why that is the case before proceeding to heavy math. Not really, his argument is that "PG's mean-post selection test (the 'PMST') is only valid if different sexes have the same distribution of abilities". If you or PG believe that the PMST is a valid way of showing that bias exists, the burden is on you to show that different sexes have the same distribution of abilities.
  - LordHumungous 11y ago
    From the Paul Graham article: >You can use this technique whenever (a) you have at least a random sample of the applicants that were selected, (b) their subsequent performance is measured, and (c) the groups of applicants you're comparing have roughly equal distribution of ability. So yes, OP is ignoring the entire premise of PG's argument.
    - zodiac 11y ago
      OP acknowledges this... "Unfortunately, using the mean as a test statistic is flawed - it only works when the pre-selection distribution of A and B is identical, at least beyond C." To me the rest of the article is asks the question, "requirement (c) is really strong, is there a way we can use post-selection statistics to determine bias while weakening (c)? what if we tried measuring the post-selection minimum instead of the mean?" Also PG edited his essay to add that disclaimer only after WildUtah's comment, so it's possible that OP hasn't read the updated version.