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>Yes, that's was I was getting at too. You shouldn't just arbitrarily toss data out because it doesn't look nice on your graph. But you might want to begin before the data-gathering stage to ensure that you're sampling exactly what you want. That is, you have to establish the focus of your sample before collecting data, not afterward. What types of homes in what neighborhoods in what timeframe, etc...
>
>And is commonly the case with samples of housing costs and salaries, for example, with very high variability, the median is very good measure of central tendancy.

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?

Marc

You anonymous pain in the ... :-)