Articulate the primary interpretations of probability theory and the role these interpretations play in Bayesian inference Use Bayesian inference to solve real-world statistics and data science ...

In the ever-evolving toolkit of statistical analysis techniques, Bayesian statistics has emerged as a popular and powerful methodology for making decisions from data in the applied sciences. Bayesian ...

Journal of the Royal Statistical Society. Series B (Statistical Methodology), Vol. 76, No. 5 (NOVEMBER 2014), pp. 833-859 (27 pages) The choice of the summary statistics that are used in Bayesian ...

This course introduces the theoretical, philosophical, and mathematical foundations of Bayesian Statistical inference. Students will learn to apply this foundational knowledge to real-world data ...

Journal of the Royal Statistical Society. Series B (Statistical Methodology), Vol. 62, No. 1 (2000), pp. 57-75 (19 pages) Hidden Markov models form an extension of mixture models which provides a ...

Alice and Bob are playing a game in which the first person to get 6 points wins. The way each point is decided is a little strange. The Casino has a pool table that Alice and Bob can't see. Before the ...

Carlin and Louis - Bayes and Empirical Bayes Methods for Data Analysis Gelman, Carlin, Stern and Rubin - Bayesian Data Analysis Bernardo and Smith - Bayesian Theory Gilks, Richardson and Spiegelhalter ...

David Vaux argues that experimental biologists should be better versed in classical statistics (Nature 492, 180–181; 2012). We suggest that they might also join the shift to Bayesian statistics that ...