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Twenty-nine research teams analyzed the same data, and they all reached different results.
(fivethirtyeight.com)
A place to share and discuss data visualizations. #dataviz
(under new moderation as of 2024-01, please let me know if there are any changes you want to see!)
Obligatory link to Statistics Done Wrong: The Woefully Complete Guide, a book on how statistics can and has been abused in subtle and insidious ways, sometimes recklessly. Specifically, the chapters on the consequences of underpowered statistics and comparing statistical significance between studies.
I'm no expert on statistics, but I know enough that repeated experiments should not yield wildly different results unless: 1) the phenomenon under observation is extremely subtle so results are getting lost in noise, 2) the experiments were performed incorrectly, or 3) the results aren't wildly divergent after all.
Thanks for taking the time to post these links, just letting you know you're efforts have benefited at least one person who's gonna enjoy reading this.