In article <[EMAIL PROTECTED]>,
Michael Granaas <[EMAIL PROTECTED]> wrote:
>On Tue, 11 Apr 2000, Robert Dawson wrote:
.................
>> and Michael Granaas responded
>> > This (point 4) is certainly what we have been lead to believe, but I
>> > question the assumption. Do we not in fact teach that we are to act as if
>> > the null is true until we can demonstrate otherwise?
>> I certainly don't. We *compute* as if the null was true, whether we
>> believe it or not; then we either conclude that (null + data) is implausible
>> or that the data are consistent with the null.
>And if the data are consistent with the null we do what? Act as if the
>null were true? Act as if nothing were true? In a pure interpretation of
>this approach we must act as if there were no knowledge (null not
>rejected) or only very weak knowledge (effect is in the ________
>direction). The first is a complete waste of effort and the second
>provides only the weakest bit of sketchy knowledge.
>Every research project should plausibly add to our knowledge base. But,
>if the null is a priori false failure to reject is just that a failure and
>waste of time.
One might think that if the null is a priori false, then
we should just go ahead and reject it without looking at
the data. But we are asking the wrong question; what is
usually wanted is to decide whether it is better to act
as if the null is true. This is the usual situation; if
statistical testing was available and used in science in
the early days, most hypotheses would have been rejected.
But without accepting a false hypothesis, it would not be
possible to draw conclusions, and progress would not be
made.
In the physical sciences, it was sometimes the case that the
data were sufficiently inexact that the error in the model
got swamped by the errors in the data; in such a case, the
null hypotheses might get through. Chemists would have had
major problems in the early days if they could weigh their
samples accurately enough; the isotope effect would mess up
the theories.
--
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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