Exoclimes Simulation Platform (ESP) Inaugural Summer School (2019)

While most nuclear-physics Ph.D. students are taught some standard (frequentist) statistics as part of their course work, very few encounter Bayesian methods until they are engaged in research. But Bayesian methods provide a coherent and compelling framework to think about inference, and so can be applied to many important questions in nuclear physics. The overall learning goal of this school is to take students who have had no previous exposure to Bayes’ theorem and show them how it can be applied to problems of parameter estimation, model selection, and machine learning.