Pope Francis in the US
Pope Francis has impressed many around the world as a remarkable and charismatic thought leader. His stature provides a giant megaphone for a range of progressive ideas touching on the environment and problems of inequality, among other contentious matters. Of course he is a revered spkesman also for conservative ideas on sexuality and other human issues.
His visit to the US over several days, beginning September 22, included ceremonies at the White House and meetings with the President on the 23rd, then on the next day, an address to both houses of Congress. On the 25th he went to New York City where he spoke to the UN and at a memorial for 9/11. On the 26th he journeyed to Philadelphia and participated in World Family Day, and on the 27th, gave a mass at the cathedral of John and Peter.
Five days is too long a period to allow a formal event designation, but it certainly was of compelling interest not only to people in the cities he visited, but around the world, so we did an exploratory analysis.
Exploratory Hypothesis and Results
We did not set a formal hypothesis for this event because of its length and its overlap with other major events in the world, but have processed the data using the standard statistical analysis. The graph below shows the result. It can be informally compared with another Papal pilgrimage, and while it does have a considerable amount of positive deviation, the last two days give a contrary picture.
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.