The death toll in the attack on a Kenyan university by extremists has risen sharply to 147 people, as the operation to free hostages being held in a dormitory there ended with the deaths of four “terrorists” involved, Kenyan officials said. The number of casualties makes it one of the deadliest terror attacks in the country's recent history. The al Qaeda-affiliated terror group al-Shabab claimed responsibility for the assault earlier today. In addition to the four purportedly killed, Kenyan authorities said another suspect was taken into custody. Most of the victims were students, Kenyan Interior Minister Joseph Nkaissery said, but two policemen, a soldier and two watchmen were also killed. The attack began at about 5:30 a.m. local time (02:30 UTC) today at Garissa University College, which is located near the country's border with Somalia, and lasted more than 13 hours. The violence started as students were preparing for their morning prayers. PHOTOS: Terrorists Attack at University in Kenya Kenya Westgate Mall Attack: What Is Al-Shabab? An unidentified student, recounting the attack to Kenya's Citizen TV, said the chaos sent innocent citizens running into harm's way. "Guys started jumping up and down, running for their lives, but it's unfortunate that where they were going to is where the gunshots were coming from," the student said.
Specific Hypothesis and Results
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 bottome 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.