How to become a Bayesian in eight easy steps: An annotated reading list

Alexander Etz, Quentin Gronau, Fabian Dablander, Peter Edelsbrunner, Beth Baribault, arXiv, Aug 18, 2017
Commentary by Stephen Downes
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I learned about Bayes Theorem while studying probability in the 1980s, but I never imagined it would have the influence it has today. It's a mechanism for calculating the probability of X given Y. For example (as Sherlock Holmes would say), if you've ruled out all the other possibilities, the probability of the one that remains, no matter how unlikely it seems, equals 1. Anyhow, I found this paper an interesting, if dense, read. Instructional designers will find the diagram of the path through 40 major papers (end of the article) interesting. It starts out with 'easy and theoretical', but at paper 4, jumps into 'really difficult and theoretical'. Is that the best path through the material?

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