1. If you use a sample larger than necessary, the costs for collecting,
processing and analyzing the data are unnecessarily increased.
2. If you take a mechanical approach to statistics, such as looking only at
"statistical significance" and not at practical significance, then you may end
up being more misled by an overly large sample than by a smaller one -- the
huge sample size alone will often lead to greater "statistical significance."
Steve Albert
===========================================================================
This list is open to everyone. Occasionally, less thoughtful
people send inappropriate messages. Please DO NOT COMPLAIN TO
THE POSTMASTER about these messages because the postmaster has no
way of controlling them, and excessive complaints will result in
termination of the list.
For information about this list, including information about the
problem of inappropriate messages and information about how to
unsubscribe, please see the web page at
http://jse.stat.ncsu.edu/
===========================================================================
