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A berserker in Oakland methodically murdered seven people and hurt many
more in yet another school shooting.
A sage I know thinks that although this event is small in terms of the
loss of life, it is symptomatic of something new and rather terrible. A
kind of disease epidemic, or in terms of a global mind, some sharply
focused malfunction or localized damage. I find that idea compelling,
and, especially since we already have a series of these small but
horrifying tragedies it seems appropriate to add this one as a formal
event in that cluster.
From time.com:
Police officers prepare to move the victims' bodies after a gunman
killed seven people at a private religious college in Oakland, Calif.,
on April 2, 2012
Oakland has the misfortune among California cities to be racked by daily
shootings and frequent bouts of violence. But the events on Monday
morning stunned even jaded crime watchers. A small religious school for
immigrants looking to improve their English and develop career skills
had suddenly become the site of one of the worst incidents of mass
killing in the entire state in recent years.
At around 10:30 a.m., a man who has now been named by police as
43-year-old One Goh, opened fire in a classroom at Oikos University.
Lucas Garcia, who teaches English as a second language there, told TIME
that he heard "half a dozen shots" before sticking his head out his
classroom door. When he heard someone shout, "He's got a gun!" he
ushered his class of about 20 students out the back door and walked with
them to the parking lot of a neighboring Walmart. The shooting was
taking place in the nursing department on the far side of the campus.
Read more:
http://www.time.com/time/nation/article/0,8599,2110909,00.html#ixzz1r1T2TPk5
The GCP event was set for 10:00 to 16:00, which includes 30 minutes
before and several hours after the shooting began. The result is
Chisquare 21462.563 on 21600 df, for p = 0.745 and Z = -0.659.
It is important to keep in mind that we have only a tiny
statistical effect, so that it is always hard to distinguish
signal from noise. This means that every "success" might be
largely driven by chance, and every "null" might include a real
signal overwhelmed by noise. In the long run, a real effect can
be identified only by patiently accumulating replications of
similar analyses.
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