By moi as well. Paper link. Abstract: The reason probability models are used is to characterize uncertainty in observables. Typically, certainty in the parameters of fitted models based on their parametric posterior […]
Kevin Gray is back with another question, this time about priors. His last led to the post “Was Fisher Wrong? Whether Or Not Statistical Models Are Needed.” (The answer was yes and […]
It’s easy to sound more certain than the evidence warrants, especially when using classical parameter-based statistical methods. I’ll show you how. I’ll give you the procedure first, then work through an example […]
Some two and a half years ago I posted this article: “An Infinity of Null Hypotheses — Another Anti-P-Value Argument“. The title is unfortunate; or, rather, the subtitle is. It should have […]
Here it is, friends, the one complete universal simple function, the only function you will ever need to fit any—I said any—dataset x. And all it takes is one—I said one—parameter! . […]
Listen to the podcast at YouTube, Bitchute, or Gab. We know all about models by now, do we not, dear readers? A model, also known as a theory, can be made about […]
This is from Gerd Gigerenzer’s “Mindless statistics” in The Journal of Socio-Economics, 33, (2004) 587–606. Have a go before looking at the answers (I’m giving my own, not quoting Gigerenzer). Send this […]
This example is derived from ongoing conversations with a colleague, and portions of this post (mathematified) might show up in a paper. The genesis of this example is from Ron Christensen’s 2005 […]
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