> Hi, Graham --
>
> It's been a long time since I've heard any discussion about
> UNDERACHIEVERS and OVERACHIEVERS. I've never been able to understand
> the discussions.
>
> NO MATTER WHAT VALUE THE CORRELATION (SLOPE OF THE REGRESSION LINE) HAS we
> know that the ALGEBRAIC SUM OF THE ERRORS IS ZERO. Now that says that
> the SUM OF THE ABSOLUTE VALUES OF THE POSITIVE ERRORS IS EQUAL TO THE
> SUM OF THE ABSOLUTE VALUES OF THE NEGATIVE ERRORS. THEN WE WOULD EXPECT
> TO OBSERVE ABOUT ONE-HALF OF THE OBSERVATIONS TO HAVE POSITIVE ERRORS AND
> ONE-HALF TO HAVE NEGATIVE VALUES.
>
> THEREFORE, FOR ALL CORRELATIONS (ZERO INCLUDED) WE SHOULD EXPECT TO
> CONCLUDE THAT ABOUT ONE-HALF OF ALL CASES
> WOULD BE CALLED "OVER-ACHIEVERS" AND ABOUT ONE-HALF WOULD BE CALLED
> "UNDER-ACHIEVERS". DOES THAT DESIGNATION HAVE ANY OPERATIONALLY USEFUL
> MEANING?
There are so many different factors that go into the amount of medals
won that it seems silly to perform a regression based upon population
and GDP to use as predictors. Organization of Olympic Committees,
training facility quality, programs for youths, weather, etc. all can
affect the number of medals won, and then there is the factor of
injuries, which to me seems like it cannot be modelled except as
random noise.
To say that half the observations should have positive errors and half
should have negative errors is to confuse median with mean.
--
Paige Miller
Eastman Kodak Company
[EMAIL PROTECTED]
"It's nothing until I call it!" -- Bill Klem, NL Umpire
"Those black-eyed peas tasted all right to me" -- Dixie Chicks
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