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

by nshepperd 11y ago

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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.

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.