--- In FairfieldLife@yahoogroups.com, Peter <[EMAIL PROTECTED]> 
wrote:
>
> 
> 
> --- off_world_beings <[EMAIL PROTECTED]> wrote:
> 
> snip
> 
> > The research
> > grant system 
> > ensures that a researcher is under pressure to prove
> > their pet 
> > theory.
> 
> Another way of saying this is that the researcher is
> attempting to disprove the null hypothesis (i.e., that
> the event is not statistically possible). So there is
> an implicit bias in the very structure of statistical
> research. But how could you get around this? 
> 

Actually, the researcher is supposed to set things up to confirm the 
null hypothesis yet leave his pet theory a way to counterdict it 
there's something there. Type II errors are when you fail to leave 
much opportunity to find an effect (rule out the null hypothesis) if 
there is one.



> > <<<When professors at the
> > >  U of Iowa attempted to do, MUM refused to
> > cooperate with them.>>>
> > 
> > When was this? Where did you hear this?
> 
> I forgot his name, he's a sociologist at the U of I.

Barry Markowski. Nice guy, but with definite anti-TM bias. Of course, 
he will say (with some justification) that his bias is legitimate.

> It is common scientific practice to allow your raw
> statistical data to be examined by other researchers.
> MIU/MUM would not allow this because, I suspect, that
> their number crunching was a little outside of normal
> limits and the data could be shown to confirm the null
> hypothesis with more conservative statistical
> analysis. This would mean that the ME, as an
> alternative explanatory hypothesis, was, at best, very
> weak, or, at worst, no explanation at all. Considering
> the radical paradigm shift of the ME, the statistical
> research used to support this alternative hypothesis
> was very weak.
> 

I can't prove you wrong, but I hope that you are.





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