Re: Collinearity, confidence intervals and sampling

reflex <sdfs@xxxxxxxxx> wrote:

Say if you had a population sample of all hospitals in England, and you
wanted to say something interesting about all hospitals in England, then you
wouldn't need to generalise to a wider population because you know the whole
population. Surely that's a real application?

There are various ways of looking at how the hospitals in England got
there!

Your are in the "They are there, so what more is to be said" camp.
Which is the least imaginative point of view of all, but the way in
which the majority of people think. So, life being what it is, a
proportion of professional statisticians think exactly like that, and
get very cross if asked to think in any other way. As similarly do a
proportion of academic/teaching statisticians.

[Remark: One view of the origins of crossness in the human mind is that
it results from the person who is cross not having any relevant concept
in his/her head to deal with the situation. The crossness emerges in
bluster, posturing, contempt ... but only rarely calms into humility!]

Another, far-richer but far-more-complex, point of view is that the
hospitals that are actually there are there as the outcome of some
hidden (partly probabilistic) process, which in re-runs of life starting
from the same point, say 50 years ago, could have turned out in a whole
variety of ways.

It would be useful to establish things about that process
- to foresee how it might develop,
- to intervene at well-judged points to change the likely outcomes.
- and just to understand how things happen.

So the intellectual challenge is to model how the hospitals got into
their present state, and to do so in ways which leaves you with a useful
model for exploring policy issues for the future.

In that sense, the current set of hospitals is simply a sample of the
"might-have-been"s to give you a clue about the future set of
"could-be"s.

I'm in the camp that thinks that if you aren't at least trying to think
in those terms you haven't begun to be potentially useful. Facts are
useless without an interpretive context.

--
Hylton
.

Relevant Pages

  • Re: Collinearity, confidence intervals and sampling
    ... >> wanted to say something interesting about all hospitals in England,>> then ... >> wouldn't need to generalise to a wider population because you know the ... > can show you that you are drawing inferences. ...
    (sci.stat.consult)
  • Re: Collinearity, confidence intervals and sampling
    ... Say if you had a population sample of all hospitals in England, ... can show you that you are drawing inferences. ... The population of interest is what you are trying to generalise to in the ...
    (sci.stat.consult)
  • Re: Collinearity, confidence intervals and sampling
    ... wanted to say something interesting about all hospitals in England, ... The population of interest is what you are trying to generalise to in the first place though isn't it? ... So in taking a random sample from a set population (hospitals in England) you can arguably generalise to all hospitals. ...
    (sci.stat.consult)
  • Re: Collinearity, confidence intervals and sampling
    ... Say if you had a population sample of all hospitals in England, ... Rich Ulrich ...
    (sci.stat.consult)