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Why Statistical Significance Is Killing Science

Analysis by Dr. Joseph Mercola Fact Checked

statistical significance

Story at-a-glance -

  • In 2016, the American Statistical Association warned against the misuse of "statistical significance" to interpret scientific research; yet another editorial in Nature, signed by over 800 researchers, now calls for the community to abandon the concept entirely
  • Statistical significance is based on P-value and confidence intervals. While meant to help researchers determine the validity of the findings, the numbers are not an accurate representation of reality and thus “waste research efforts and misinform policy decisions,” Nature says
  • The risk of an action taken or not taken is often expressed without explanation of whether it is absolute risk, able to stand alone, or relative risk, determined by comparing the experimental and control groups. Too often the relative risk offers a distorted view of the results
  • When profits depend on the risk ratio published and not an accurate representation of the risk of taking the experimental drug, it becomes clear that making lifestyle changes to improve your health may be your best option. Making small changes over time to your sleep, nutrition and exercise habits reaps significant rewards

In 2016, the American Statistical Association released an editorial warning against the misuse of statistical significance in interpreting scientific research. Another commentary was recently published in the journal Nature, calling for the research community to abandon the concept of statistical significance.

Before being published in Nature, the article states it was endorsed by more than 800 statisticians and scientists from around the world. Why are so many researchers concerned about the P-value in statistical analysis?

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