On Tue, 15 Jan 2002 23:06:25 GMT, janne <[EMAIL PROTECTED]> wrote: > Lets say I do a x2(chi) test and have the hypothesis: > [snip, some example] > > If you can have < in hypothesis, then when is it < and when is it > I > should use? How do I know which one to use? > > I also wonder about t-tests the same question. When do I know if I > should use < or >?
Are you referring to the chisquared test on a contingency table? That is the most popular thing called 'chi-squared test' but it is far from the only thing. Almost always (but not always), chisquared is used to 'reject' when the chisquared value is large. Now, if your H0 and Ha require "less than," that is a pretty good indicator that you should *not* be using the contingency table; but you might be using a 'test for proportions' that gives you the square root of a 1-d.f. chi-squared, which is a normal-deviate z: which has either a plus or minus sign attached. But you *can* use the chisquared test, and make sure the differences are in the right direction. Short answer: Look at the numbers, and use your head. There is not a magical formula that makes a stupid-looking answer come out to be correct. If this still seems confusing, borrow a book or two on experimental design and spend time on the earliest chapters. -- 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/ =================================================================
