

US Officer Involved Shootings, Mapped - dhammer
http://hiddentao.github.io/ois-incidents-map/

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politician
Clicking through randomly, it seems that the armed victims were less likely to
be killed than the unarmed victims. I wonder if the underlying data refutes
that observation.

~~~
giarc

               Killed   Not Killed

Armed________729______300

Not Armed_____211_____114

The Chi-square statistic is 4.0812. The P value is 0.043363. This result is
significant at p < 0.05

~~~
jrapdx3
Yes, armed vs unarmed were different, question is in what direction. IOW were
those armed more likely to be killed than the unarmed?

For armed "shootees", killed/not-killed == 2.43, whereas unarmed == 1.85.

Looking at it the other way, for those killed, ratio of armed/unarmed was
3.45, but only 2.63 for shooting survivors.

Since the categorical data was shown to differ significantly, the difference
ratios are also significant. We can conclude one is more likely to be shot
dead if armed when confronted by police.

Edit: grammar

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e40
If only the data underlying this visualization were complete.

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daveloyall
The data is useless. My home city has had >0 OIS during the date range, but
the data reports zero.

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dhammer
well, not useless. at least it exposes the complete lack of transparency. it's
crazy that we have to cobble together stats from news reports, rather than
official reports. that's the point. [http://www.danham.me/r/2015/01/02/ois-
api.html](http://www.danham.me/r/2015/01/02/ois-api.html)

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athenot
Suggestion: try semi-transparent bubbles for each data point. It will create a
heat map which is faster to read and understand than summaries per region.

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bengali3
See Framingham Massachusetts. Same victim listed 3 times.

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Koldark
I wonder what the data source(s) are?

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dhammer
philadelphia and dallas report official stats, other than that, we use the
deadspin project [http://www.danham.me/r/2015/01/02/ois-
api.html](http://www.danham.me/r/2015/01/02/ois-api.html)

