- just a note on z-tests - On 3 Nov 2003 07:37:58 -0800, [EMAIL PROTECTED] (Robert J. MacG. Dawson) wrote:
[ ... ] > > Ninety-nine times out of 100 when people refer to a "Z test" they do > not mean the theoretically-justified-but-very-rare test with known > variance, but a badly-done t test, in which quantiles of Z are used > where those of t should be, that was once taught as "the right thing to > do" when n was greater than 30. Who does that? Is it just the old folks went to school 35 years ago? Here is where I see expect the z-test, and it is appropriate, too. Consider all those non-parametric statistics, which so often reduce down to a 1-df chisquared. It is 1-df chisquared, because it is Normal at the root. X2= Normal-squared. You often can describe, if it matters to you, the 'one-tailed' version of the test. Naturally, that will be Normal. Unlike the situation with 'normally distributed data,' the *variance is known* when you have a binomial, or multinomial, or rank-order distribution with no ties. That is why the subsequent test can be z, rather than t. -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html "Taxes are the price we pay for civilization." . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
