False Alarm Missile Attack Hawaii
HAWAII SOUNDS WARNING SIRENS AMID NUCLEAR THREATS FROM NORTH KOREA
Hawaii Gov. David Ige said there wasn't a process in place to send out a message stating that "this is a false alarm." ... "You know, we were not prepared for that, the fact that an alert was issued that was incorect," Ige said. "So we have that built now."
At about 8:07 a.m. local time, Hawaii citizens received an emergency alert on their phone that read: “BALLISTIC MISSILE THREAT INBOUND TO HAWAII. SEEK IMMEDIATE SHELTER. THIS IS NOT A DRILL.”
It took almost 15 minutes to get the word out that it was a false alarm, and longer for the word to spread. At 8:20 a.m. local time, Hawaii EMA tweeted that there was “NO missile threat” to the state. However, the tweet didn't reach people who aren't on the social media platform. Around the same time, House Rep. Tulsi Gabbard, D-Hawaii, tweeted: “HAWAII – THIS IS A FALSE ALARM. THERE IS NO INCOMING MISSILE TO HAWAII. I HAVE CONFIRMED WITH OFFICIALS THERE IS NO INCOMING MISSILE.” Roughly 15 minutes later, the U.S. Pacific Command issued a statement, clarifying there was "no ballistic missile threat to Hawaii."
Specific Hypothesis and Results
The GCP hypothesis was set for 6 hours beginning at 8:00 am local time in Hawaii, a few minutes before the alarm was set off. While this isn't an event with tragic outcomes, it certainly was terribly frightening for more than a million people in Hawaii. The result is Chisquare 21410 on 21600 df, for p = 0.819 and Z = -0.912.
The data look like a normal random walk around the time people were most concerned, and only later take on a consistent trend. Thus there is no indication of a global consciousness effect in the sense of our formal prediction. As noted in the caveat below, no single event can be reliably interpreted. But we hope there will be no repeats that would allow further testing.
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.