Syria Bombing April 2018

From the New York Times: WASHINGTON — The United States and European allies launched airstrikes on Friday night (Eastern time) against Syrian research, storage and military targets as President Trump sought to punish President Bashar al-Assad for a suspected chemical attack near Damascus last weekend that killed more than 40 people.

Britain and France joined the United States in the strikes in a coordinated operation that was intended to show Western resolve in the face of what the leaders of the three nations called persistent violations of international law. Mr. Trump characterized it as the beginning of a sustained effort to force Mr. Assad to stop using banned weapons, but only ordered a limited, one-night operation that hit three targets.

Defense Secretary Jim Mattis, who had urged caution in White House deliberations leading up to the strike, told reporters on Friday night that there were no more attacks planned unless Mr. Assad again uses gas on his own people.

Specific Hypothesis and Results

The GCP event was set for 6 hours beginning at 8 PM, one hour before the attack. This corresponds to 03:00 in Damascus. The result is Chisquare 21849 on 21600 df, for p = 0.116 and Z = 1.194.

Interpretation

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.

Standard caveat

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.