At 10:32 AM 4/17/00 -0300, Robert Dawson wrote:
> There's a chapter in J. Utts' mostly wonderful but flawed low-math intro
>text "Seeing Through Statistics", in which she does much the same. She
>presents a case study based on some of her own work in which she looked at
>the question of gender discrimination in pay at her own university, and
>fails to reject the null hypothesis [no systemic difference in pay between
>male and female faculty]. She heads the example "Important, but not
>significant, differences in salaries"; comments (_perhaps_ technically
>correctly but misleadingly) that "a statistically naive reader could
>conclude that there is no problem" and in closing states:
the flaw here is that ... she has population data i presume ... or about as
close as one can come to it ... within the institution ... via the budget
or comptroller's office ... THE salary data are known ... so, whatever
differences are found ... DEMS are it!
the notion of statistical significance in this case seems IRRELEVANT ...
the real issue is ... given that there are a variety of factors that might
account for such differences (numbers in ranks, time in ranks, etc. etc.)
.... is the remaining difference (if there is one) IMPORTANT TO DEAL WITH ...
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