In article <[EMAIL PROTECTED]>,
dennis roberts <[EMAIL PROTECTED]> wrote:
>At 02:22 PM 8/22/00 -0500, Herman Rubin wrote:
>>No geographer would take the heights of mountains and
>>convert them to a probability scale.
>i beg to differ ... for, it is not totally an uninteresting question that
>someone might ask ... for all mountains ... what is the p value for
>selecting at random from all mountains ... one that is a height of 10,000
>feet or more ...
One might want to know the distribution, but which distribution?
And unless someone was claiming to have selected a mountain
"at random", who would use it for inference purposes.
>or, just to ask: what would a frequency distribution look like for all
>mountains ... say ... where the scale on the baseline goes from 0 to 2500,
>2501 to 5000, etc. ...
This discretization is likely to make the distribution of little
value, but in any case, it would be best as a frequency count,
not a proportional count.
>good geographers ... would/should have some knowledge of this ... not that
>they would spend their lives doing these tabulations but, it is part of the
>knowledge base in which they work
>if you have lived ONLY in pennsylvania ... some mountains look pretty TALL
>while others seem rather short ... while, to those who have lived in
>florida all their lives (and never seen pictures or surfed the WWW) ... ALL
>of these look like the alps ... but, if you lived in the alps ... the
>mountains of pennsylvania, even the tallEST ones, look like little bumps
>on the horizon
But if they were investigating a model in which the height
of the mountain was a determining variable, using the Pennsylvania
distribution would limit the applicability of the model to
Pennsylvania, using the Colorado distribution would limit it
to Colorado, using the Peru distribution would limit it to
Peru, and one would really have nothing more than a collection
of empirical results, giving no understanding.
On the other hand, a model using height in feet or meters could
be considered for general use. It would not have to be tailored
for the individual location.
--
This address is for information only. I do not claim that these views
are those of the Statistics Department or of Purdue University.
Herman Rubin, Dept. of Statistics, Purdue Univ., West Lafayette IN47907-1399
[EMAIL PROTECTED] Phone: (765)494-6054 FAX: (765)494-0558
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