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Surprising Science

Science Needs Better Statistical Analysis

Statistical analysis must find ways to expose and counterbalance all the many factors that can lead to falsely positive results — among them human nature and the effects of industry money.
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A respected psychology journal’s decision to accept a research report that claims to show the existence of extrasensory perception has inflamed one of the longest-running debates in science. Some statisticians have argued that the standard technique used to analyze data in much of social science and medicine overstates many study findings — often by a lot. The literature is littered with positive findings that do not pan out: “effective” therapies that are no better than a placebo; slight biases that do not affect behavior; brain-imaging correlations that are meaningless. …Statistical analysis must find ways to expose and counterbalance all the many factors that can lead to falsely positive results — among them human nature…and industry money.

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The problem of scientists manipulating data in order to achieve statistical significance, labelled p-hacking is incredibly hard to track down due to the fact that the data behind statistical significance is often unavailable for analysis by anyone other than those who did the research and themselves analysed the data.

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