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There are lots of discussions and explanations of what it means to be "Bayesian," but I think the best thing to do is jump in and start building models. That is

There are lots of discussions and explanations of what it means to be "Bayesian," but I think the best thing to do is jump in and start building models. That is how I came to understand the utility of Bayes. If you're looking for a place to start I'd go to Andrew Gelman's introduction for the Stan Language: https://www.youtube.com/watch?v=T1gYvX5c2sM https://www.youtube.com/watch?v=T1gYvX5c2sM There are Stan implementations in R, Python, Julia or you can run it in C++ since it's written in C++. I think this has greater potential to change how we deal with the unknown than AI or other machine learning.

marmaduke 9y ago
Those are interfaces not implementations of Stan, in R, Python et al. The whole Stan thing is C++, fwiw.
nonbel 9y ago
>"There are lots of discussions and explanations of what it means to be "Bayesian," but I think the best thing to do is jump in and start building models." I highly agree, just play with Stan or JAGs and you will figure it out. The prose descriptions just cannot convey the power and flexibility of Bayesian stats. PS, you shouldn't be trying to do a "bayesian t-test" or anything like that. That whole way of thinking about research (asking "is there an effect?") is flawed and can't go away soon enough.