Abstract
A common misconception in statistics is that a lack of statistical significance (P .05) onstitutes proof of no effect. In fact, this conclusion does not follow. Just as large samples ay yield small P values even when effects are trivial, important effects may miss statistical ignificance if the sample size is small, the outcome is rare, or the variability is high. This rticle reviews false-negative results and statistical power, the meaning of null results, and ow one should approach “proving a negative.”
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
