In article <[EMAIL PROTECTED]>, Alan McLean <[EMAIL PROTECTED]> wrote:
>Radford and I effectively made two different assumptions - I that the >population of interest was the population measured, he that it it was >wider than the population measured. With my assumption the t test is >not relevant; with his, its relevance depends on whether the >(sub)population measured can reasonably be considered a random sample >from the population of interest. Whether the t test in particular is the right tool is a detailed technical issue that would depend on such things as whether it is reasonable to regard the employees as independent (versus, for instance, a whole group of same-sex friends having been hired by the company, because one of them got hired and told the others how nice it was.) Regarding the more basic question of whether testing for statistical significance is sensible at all, this does of course depend on what one assumes is the population of interest. However, the recurring posts on this topic seem to almost always be for situations in which testing for significance IS appropriate, but somebody starts thinking too hard, saying, "but we've got data on everyone..." My guess is that situations where testing for significance is NOT appropriate are usually so obvious that nobody gets confused. For instance, suppose that the company is faced with a possible court ruling (sensible or not) that would require it to raise the salaries of female employees to the point where their average is the same as that of the men. The company wants to know how much their payroll would increase if this happened. They collect data on all the salaries, and from that figure out what the payroll increase would be. Nobody would be silly enough to say - "Wait! The difference between male and female salaries isn't statistically significant, so maybe this court ruling won't cost us anything at all..." 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/ . =================================================================
