--- In FairfieldLife@yahoogroups.com, "sparaig" <[EMAIL PROTECTED]> wrote:
>
> > And the comment, "this is precisely the type of sporadic fluctuation
> > one must account for when total numbers are small." Exlusion is a
> > major way of "account[ing] for" such outliers. 
> 
> 
> It was NOT excluded from the data. The weekly AVERAGE was the weekly
average with no 
> data excluded. The SIGNIFICANCE of the outlier was dismissed because
it was only one 
> data point amongst many and wasn't repeated and in fact was reversed
the next week (20 
> one week and 4 the next).

See footnote 3.

   3. After removing the outlier of June 22, Poisson regression
analysis indicated there was no significant difference in the level of
homicides in June and July 1993 from the remainder of the year.

-- 
This implies that WITH the outlier included, there WAS a significant
difference [higher] in the level of homicides in June and July 1993
from the remainder of the year.

And at best, the ME had no effect on murders. At worst, it increases
them -- assuming ME is causal. So it would appear, ME is
"crime-stopper light". Works best, thjough modestly, on lighter-weight
crimes I guess. And even then, its not a huge decrease. I wonder if
SSRS or AMMA can provide a heavy duty crime fighting effect. :)

By the way, I assume each diamond on chart II is one week. If so,
there was a sizable drop in HRA crimes in week 9 and 10, AFTER the
course. Which sort of disturbs the immediadiacy of the ME and that
"This shows that usually the violent crime levels were directly
proportional to temperature — and therefore that violent crime could
be accurately predicted from the previous pattern in the data."

Of course you could postulate a lag effect -- which I have for the
financial markets impacts -- but then you have to discount the drops
in weeks 1 and 2. Which occurred by the way, just after a large spike
pre-course. So much for very strong temperature correlated crime trends. 





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