Bayesian Stats?

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As a math undergrad, I only get to take so many stats courses. Most quant programs say they wanna see a course in probability, and then also statistics more broadly. I wanna take it a step further. I have a basic/broad stats class, and a hardcore forecasting focused class in R, and also a stochastic processes course. Is Bayesian stats a good supplement to this layout, or could I focus my time better in like..."mathematical statistics" or "experimental statistics"?
 
My two cents. I think all things Bayesian would be a good investment. You see it being used in many applications, e,g. Bayesian networks, heuristic searching and parts of statistical learning. See the book by Hastie, Tibshirani and Friedman (Springer).
That's why I would if I were back at school again. As well as a decent grounding in function approximation (numerical analysis) as it is the basis for all this stuff. Crucial IMO.

Understanding why and how these methods works helps.
 
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