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inventingsituations.net | ||
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emiruz.com
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jaketae.github.io
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| | | | | So far on this blog, we have looked the mathematics behind distributions, most notably binomial, Poisson, and Gamma, with a little bit of exponential. These distributions are interesting in and of themselves, but their true beauty shines through when we analyze them under the light of Bayesian inference. In today's post, we first develop an intuition for conditional probabilities to derive Bayes' theorem. From there, we motivate the method of Bayesian inference as a means of understanding probability. | |
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aurimas.eu
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| | | | | a.k.a. why you should (not ?) use uninformative priors in Bayesian A/B testing. | |
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errorstatistics.com
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| | | David Cox's famous "weighing machine" example" from my last post is thought to have caused "a subtle earthquake" in foundations of statistics. It's been 11 years since I published my Statistical Science article on this, Mayo (2014), which includes several commentators, but the issue is still mired in controversy. It's generally dismissed as an annoying,... | ||
