In article <[EMAIL PROTECTED]>, Dennis Roberts <[EMAIL PROTECTED]> wrote:
>the fact is in this case ... there is either a difference in salaries (for >which they have the data) or not > >let's say for argument ... that there is a difference in favor of males ... >of $1000 a year ... but, because there is wide variation within the male >and female categories (because of years of experience) ... a t test fails >to reject the null > >what is the data analyst going to say ... that there is no difference ... >??? how can you use the t test RETENTION of the null to persuade the >females that the $1000 dollars is just a figment of their imagination? > >we know there is a difference ... this issue then is ... is the difference >important ENOUGH that the company/organization ... should do something >about it? a t test is NOT going to help resolve that problem > >therefore ... i claim in this kind of a situation ... the FACTS are known >and ... an inferential test like a t test is completely inappropriate If the company has a policy of paying all employees in this position the same salary, then, of course, if a woman discovers that she's paid $1000 less than the men, she has cause for complaint. This is obvious, and is presumably not the issue being discussed. Instead, we must assume that the company has a policy of paying these employees different amounts, based on merit. If we further assume that there is no reason why merit should be related to sex, we would expect that the average salary of men and women would be the same, IF THERE WERE NO CHANCE VARIATION. But of course there is chance variation. Even if men and women are equally meritorious on averge, the company may happen to have hired more good men than good women. To take the extreme case, suppose the company has only two employees, one male and one female. The male is paid $70,000. The female is paid $65,000. An obvious case of discrimination? Not if pay is supposed to be merit based and we have no knowledge of the degree of merit of these two employees. Radford Neal ---------------------------------------------------------------------------- Radford M. Neal [EMAIL PROTECTED] Dept. of Statistics and Dept. of Computer Science [EMAIL PROTECTED] University of Toronto http://www.cs.utoronto.ca/~radford ---------------------------------------------------------------------------- . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
