> > > For example: Quote: 
> > > "Hagelin's study used time series analysis to rule out a long 
> list 
> > of 
> > > alternative explanations, including weather variables, seasonal 
> > > effects, changes in police surveillance, and trends and cyclical 
> > > patterns inherent in the crime data."
> > > http://istpp.org/crime_prevention/voodoo_rebuttal.html
> > > 
> > > OffWorld.
> > >
> > 
> > Assuming that this is the case, that still doesn't rule out some 
> > OTHER factor that wasn't considered, like I said...>>>
> 
> Yes it does. This is how statistical analysis works. It minimizes 
> the probability that it is due to some other factor, than the one 
> being observed.

The raw data in the DC study did not show any statistical validity, so
Hagelin adjusted the data by a "heat factor" arguing that the weather
was hotter than avg and thus the crime rate should have been higher
than avg.  This is how he got his statistical proof.  And this is why
studies conducted by people with an obvious bias in the outcomeare
generally not taken too seriously by scientific community as they
typically massage the data and the type of statistical analysis used
in order to get the conclusion they want.  The maharishi effect is
still waiting for an independent verification.  When professors at the
 U of Iowa attempted to do, MUM refused to cooperate with them.








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