the opinions of both i highly respect
so, what is the original inquirer to do?
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
At 09:49 AM 4/4/03 +1000, Alan McLean wrote:
If the population means are known and being compared, then any difference must be significant! No need for any test.....
Alan
On Friday, April 4, 2003, at 05:31 AM, Rich Ulrich wrote:
On 3 Apr 2003 19:13:43 GMT, trw7atixdotnetcomdotcom (Tim Witort) wrote:
I'm developing a report in an analysis program. This report examines employee salaries - comparing the salaries of men to those of women in a particular job title in a particular company. The goal is to determine if the difference in their mean salaries is statistically significant.
I have been directed to the t-test to gather this information. When I look at the t-test, however, it appears to be geared toward *estimating* the difference in the means of a population based on a *sample* of the population. Since I am using the entire population, can I still use the t-test to determine if the difference in the means is statistically significant? Is there another test that should be used instead?
Use the regular t-test.
There is such a thing as correction for "finite population" but it is hardly ever appropriate.
It certainly is not, in the instance *you* describe: With 100% sampled, there is no "correction"; *you* would simply conclude A is greater than B whenever A is measured as greater than B.
Taking votes and ordering supplies... you might use a finite-sample correction to further those purposes, if you have a survey that is (a) incomplete; and (b) randomly chosen, for what is complete.
You can use groups.google.com , advanced, to look in the sci.stat.* groups for the topic.
-- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html .. .. ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: .. http://jse.stat.ncsu.edu/ . =================================================================
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Dennis Roberts, EdPsy, Penn State 208 Cedar Bldg. AC 8148632401 Email: <mailto:[EMAIL PROTECTED]> Web: http://roberts.ed.psu.edu/users/droberts/drober~1.htm
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