Just because Dennis has trouble with the null hypothesis, that does
not mean that it is a bad idea to use them.
On 10 Apr 2000 08:41:06 -0700, [EMAIL PROTECTED] (dennis roberts)
wrote:
> the term 'null' does NOT mean 0 (zero) ... though it is misconstrued that way
>
> the term 'null' means a hypothesis that is the straw dog case ... for which
> we are hoping that sample data will allow us to NULLIFY ...
- this seemed okay in the first sentence. However, I think that
"straw dog case" is what I would call "straw man argument" and that
is *not* the quality of argument of the null. The point-null is
always false, but we state the null so that it is "reasonable" to
accept it, or to require data in order to reject it.
> in some cases, the null happens to be 0 ... but in many cases, it does not
>
> cases in point:
>
> 1. null hypothesis is that the population variance for IQ is 225
< snip, similar stuff, and other stuff>
-- I think I reject the null when it is stated, " ... is 225". Sure,
the point-null is false. But state it, "The difference between the
Variance and 225 is zero" -- and then, you require data to show that
there is evidence, that difference should be accepted as other than 0.
We either *accept* that the difference is (may be) zero, or we
*reject* and have some other difference. We do not *conclude* that
the difference is zero.
There have been posts in the last two weeks on sci.stat.consult
concerning the testing of bioequivalence -- and that is a case where
the null is more complicated. Generally, the ALTERNATIVE is that the
new drug falls between 80% and 125% of the potency of the old drug.
(Those are the limits that the FDA cares about.) The null is that the
new is Greater than 125% or Less than 80% of the old.
If we have rotten evidence, with bad means, or huge standard
deviations, then we have to accept the null; the new may be unlike the
old. That is not a weak "strawman" - that is a reasonable, default
alternative. The standard testing is called Two One Sided Tests, to
show that the amount is definitely less that the Upper limit, and
definitely greater than the lower. Basically, you need to construct a
Confidence interval on the difference and have it fall completely
within the limits.
--
Rich Ulrich, [EMAIL PROTECTED]
http://www.pitt.edu/~wpilib/index.html
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