> > > >Interesting. But excuse me for asking: Is this not kind of a > self-fulfilling truth, somehow given in by practical calculation > contstraints? Oh! acceptable under field conditions of course, but > theoretically, you would have a hard time validating this no? > > > >You anonymous pain in the ... :-) > > Well, I am a bureaucrat, is that not my position to be a pain in the...? > :~) Eehr, Bruce, I am sorry. This is not what I meant, and certainly not to insult you. I thought I had written : Your anonymous ...., as a wink at your own signature. So if anybody is a pain ..., it's me. Sorry for the mix up. That'll teach me to try to be funny! :-) > > You don't have to know your distribution before selecting a sample, you > just have to have clear guidelines as to what to sample. You test for > sampling distribution after sampling if you don't have prior knowledge. > > The median is not the greatest measure statistically, you would always > prefer the mean, but if distribution is non-normal, the median is a better > simple measure. Non-parametric methods may be better, but they aren't so > great for the statistical novice...as it happens, housing prices are > generally non-normal and median is the generally accepted measure... I agree, but I guess the usefulness of the median must decrease these days, because calculation constraints are less relevant. If you are going to build some software I my idea would be to use the mean, or any other standard statistical entity, be it only because it is easier to validate theoretically. Regards, ... and apologies, Marc