What does it mean if research is statistically significant?
Statistical significance refers to whether any differences observed between groups being studied are “real” or whether they are simply due to chance. Statistical testing starts off by assuming something impossible: that the two groups of people were exactly alike from the start.
Why is statistical significance important in science?
“Statistical significance helps quantify whether a result is likely due to chance or to some factor of interest,” says Redman. When a finding is significant, it simply means you can feel confident that’s it real, not that you just got lucky (or unlucky) in choosing the sample.
Who are the scientists rise up against statistical significance?
Scientists rise up against statistical significance Valentin Amrhein, Sander Greenland, Blake McShane and more than 800 signatories call for an end to hyped claims and the dismissal of possibly…
Is it sensible to abandon statistical significance in science?
Amrhein V, Gelman A, Greenland S, McShane BB. 2019. Abandoning statistical significance is both sensible and practical. PeerJ Preprints 7:e27657v1. https://doi.org/10.7287/peerj.preprints.27657v1
Why is there so much focus on statistical significance?
On top of this, the rigid focus on statistical significance encourages researchers to choose data and methods that yield statistical significance for some desired (or simply publishable) result, or that yield statistical non-significance for an undesired result, such as potential side effects of drugs — thereby invalidating conclusions.
Do you publish results if they are statistically significant?
All results should be published, regardless of whether they are “statistically significant” or not. Hopefully more journals will follow JAMA [1] in not using “statistical significance” as an editorial criterion for publication of important studies. Pre-specified analyses help reduce selective and distorted reporting.