Re-examining the statistical methods used in the studies of precognition. Conclusions should not be drawn from a series of 50-50 tests and then to sift the data for anomolies. That might be the first part but then you have to run tests and analysis to confirm the anomolies.
In eight out of nine studies, Bem reported evidence in favor of precognition. As we have argued above, this evidence may well be illusory; in several experiments it is evident that Bem’s Exploration Method should have resulted in a correction of the statistical results. Also, we have provided an alternative, Bayesian reanalysis of Bem’s experiments; this alternative analysis demonstrated that the statistical evidence was, if anything, slightly in favor of the null hypothesis. One can argue about the relative merits of classical t-tests versus Bayesian t-tests, but this is not our goal; instead, we want to point out that the two tests yield very different conclusions, something that casts doubt on the conclusiveness of the statistical findings.
Although the Bem experiments themselves do not provide evidence for precognition,
they do suggest that our academic standards of evidence may currently be set at a level that is too low.
It would therefore be mistaken to interpret our assessment of the Bem experiments as an attack on research of unlikely phenomena; instead, our assessment suggests that something is deeply wrong with the way experimental psychologists design their studies and report their statistical results. It is a disturbing thought that many experimental findings, proudly and confidently reported in the literature as real, might in fact be based on statistical tests that are explorative and biased. We hope the Bem article will become a signpost for change, a writing on the wall: psychologists must change the way they analyze their data.
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Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
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