![]() For instance, the Nostradamus lines that supposedly predicted 9/11 were taken from three separate and unrelated passages and a fictional line was added. Nostradamus' quatrains are often liberally translated from the original (archaic) French, stripped of their historical context, and then applied to support the conclusion that Nostradamus predicted a given modern-day event, after the event actually occurred. This fallacy is often found in modern-day interpretations of the quatrains of Nostradamus.Attempts to find cryptograms in the Bible, and the Quran Code.This could be explained as an example of the fallacy because passages which do not match the algorithm have not been accounted for. Attempts to find cryptograms in the works of William Shakespeare, which tended to report results only for those passages of Shakespeare for which the proposed decoding algorithm produced an intelligible result.Subsequent studies failed to show any links between power lines and childhood leukemia, neither in causation nor even in correlation. over 800, was so large that it created a high probability that at least one ailment would exhibit statistically significant difference just by chance alone. The problem with the conclusion, however, was that the number of potential ailments, i.e. The study found that the incidence of childhood leukemia was four times higher among those that lived closest to the power lines, and it spurred calls to action by the Swedish government. ![]() The researchers surveyed everyone living within 300 meters of high-voltage power lines over a 25-year period and looked for statistically significant increases in rates of over 800 ailments. For example, if one wants to show that some food has a health benefit, one could take a sample of people who started eating that food and. From this reasoning, a false conclusion is inferred. A Swedish study in 1992 tried to determine whether or not power lines caused some kind of poor health effects. The Texas sharpshooter fallacy is an informal fallacy which is committed when differences in data are ignored, but similarities are overemphasized.
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