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The Wenchuan Earthquake

As can be seen from the animation, the earthquake affected most strongly two counties: Wenchuan, Beichuan. The county inbetween the two and intersecting the area of the fault is Mao county. Mao is only one syllable. Speech and print favors two syllable names and so it is extended to the form Maoxian, formally Mao county, the Xian suffix meaning county. On the animation map, the labels Wenchuan, Maoxian, and Beichuan refer to county areas.

Wenchuan Earthquake Beichuan 7 Iyar
Earthquake Animation For The First 80 Seconds

The greatest number of lives lost and buildings damaged occured in Wenchuan and Beichuan county. Had we reasoned this out before we began our experiments, we would have done an experiment using the key words: Wenchuan, Beichuan, Earthquake, China, the 6 forms for the date Iyar 7 in one experiment, and the two forms for the year 5768 in another experiment. We would have had the hypothesis that one of the 6 key word sets in the first experiment is encoded and one of the 2 key word sets from the second experiment is encoded. We would have tested the Null hypothesis of no Torah code effect against our alternative hypothesis. Using expected number of ELSs set to 75, the probability that a text from the ELS random placement text population would have as good a combined score, on a trial by trial basis, as the Torah text is 43.5/1,000, a result that we would regard in this context as weakly statistically significant.

Wenchuan Earthquake Beichuan 7th of Iyar
The search produced a cylinder size of 643. With expected number of ELSs set to 75, the probability that a text from the ELS random placement text population would produce a table as compact as that produced by the Torah text is 41.5/1,000.
Finding by Professor Haralick
Wenchuan Earthquake Beichuan 5768
The search produced a cylinder size of 856. With expected number of ELSs set to 75, the probability that a text from the ELS random placement text population would produce a table as compact as that produced by the Torah text is 21.5/1,000.
Finding by Professor Haralick