Hi: I am new to the list and have a question about bootstrap hypothesis testing. I am testing the equality of two means according to Algorithm 16.2 in An Introduction to the Bootstrap by Efron and Tibshirani (1993). They define the estimated ASL as #{t(x*b) >= tobs}/B. It seems to me that this is a one sided estimated ASL. I can easily determine the significance or lack or significance by changing the order of the means I subtract. My question is why is the ASL defined as >=? Why would I not wish to examine both ends of the null distribution? Thanks for your help. Joe Joe Horton Psychology and Social Sciences Department 7373 Admiral Peary Highway Mount Aloysius College Cresson, PA 16630 (814) 886-6437 [EMAIL PROTECTED] ================================================================= Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =================================================================