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Statistical significance is required, but not sufficient to prove an effect. Lack of statistical significance means you did not prove an effect, but you also d
by kbutler 8y ago
Statistical significance is required, but not sufficient to prove an effect. Lack of statistical significance means you did not prove an effect, but you also didn't prove there is no effect.
So the answer is more likely "statistical significance and more" rather than "ditch statistical significance".
- headsoup 8y agoI think maybe you didn't read the article. This is addressed constantly through it. Or are you just summarising?
- pmoriarty 8y agoFrom the HN Guidelines: "Please don't insinuate that someone hasn't read an article. "Did you even read the article? It mentions that" can be shortened to "The article mentions that."" https://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newsguidelines.html
- deleted 8y ago[deleted]
- BenoitEssiambre 8y agoIt's such a weak test that while you may use it informally, it should rarely be included in publications.
- joe_the_user 8y agoThis: When we're talking about how to take data as implying X, what is needed is: [logical reason to believe position, how the data was chosen to not bias the whole process, etc] + [data above threshold]. The data that a scientist gets "lives" inside one or another experimental box, some area. But unless the scientists also takes into account how that box and that data came to be, the scientist cannot make any definitive statement based on the properties of just the data. The statement "Correlation does not [automatically] imply causation" and "Extraordinary claims require extraordinary evidence" both reflect this.