Parkland School Shooting, 15 Feb 2018
From NYT: PARKLAND, Fla. — The suspect in one of the deadliest school shootings in modern American history confessed to the police that he “began shooting students that he saw in the hallways and on school grounds,” according to a police arrest report released Thursday.
The suspect, Nikolas Cruz, 19, carried a black duffel bag and backpack, where he hid loaded magazines, the report said. He arrived at Marjory Stoneman Douglas High School in Parkland in an Uber at 2:19 p.m. on Wednesday and pulled out a semiautomatic AR-15 rifle, according to details described by the authorities at a news conference on Thursday.
Mr. Cruz also shot people inside five classrooms on the first and second floors of the freshman building. He eventually discarded the rifle, a vest and ammunition in a stairwell, blended in with fleeing students and got away, the authorities said.
It is so awful it is hard to bear, the more so because it is yet another, after a dozen of these heartbreaking murderous rampages. It is, most sane people believe, not inevitable as the NRA and many bought-and-paid-for politicians, mostly Republican, want us to believe.
Specific Hypothesis and Results
The GCP hypothesis was the standard 6 hour period beginning at 2:00 pm local time, about 20 minutes before the shooting began. This is 20:00 to 02:00 UTC. The result is a marginally significant deviation, with Z = 1.605 and p = 0.054.
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.