Massacre in Las Vegas
Police Identify Lone Las Vegas Shooter As Stephen Paddock
The slain gunman police described as the “sole aggressor” in the mass shooting at a Las Vegas concert has been identified as Stephen Paddock, 64, of nearby Mesquite.
Early reports said SWAT team shot the “sole aggressor” of the mass shooting to death. Later the police said Paddock killed himself.
Paddock opened fire from the upper floors of the Mandalay Bay Hotel, killing at least 50 and injuring more than 200 around 10:15 p.m. during a performance by Jason Aldean at the Route 91 Harvest Festival, authorities said Monday. As of Tuesday morning October 3, the death toll is 59 with 527 injured.
The chaos was palpable, but also the innumerable acts of personal heroism. And the official responses from police, fire departments, and other first responders were exemplary, saving lives and rescuing people from the dire situation.
At this time, Tuesday, there is still no explanation or understanding of what motivated Paddock. It is however a case study in the ongoing debates about gun control measures. There were apparently 23 weapons in the hotel room, and thousands of rounds of ammunition. Several of the weapons were full automatic military grade rifles. There is no doubt the massacre was planned and prepared.
Specific Hypothesis and Results
This exploratory analysis takes the usual protocol of 6 hours beginning about the time of the event. The shooting began about 10:15 Las Vegas time, and the GCP event was set for 10:00 PM (0500 to 1100 UTC). A second exploration looks at the full UTC day, providing some context for the event.
The following graph is a visual display of the statistical result. It shows the second-by-second accumulation of small deviations of the data from what’s expected. Our prediction is that deviations will tend to be positive, and if this is so, the jagged line will tend to go upward. If the endpoint is positive, this is evidence for the general hypothesis and adds to the bottom line. If the endpoint is outside the smooth curve showing 0.05 probability, the deviation is nominally significant. If the trend of the cumulative deviation is downward, this is evidence against the hypothesis, and is subtracted from the bottom line. For more detail on how to interpret the results, see The Science and related pages, as well as the standard caveat below.
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.