Invited talk: Distributions for Parameters

Jul 13, 2020



There has been considerable recent controversy over the use of p-values and the phrase “statistically significant”, both in subject matter settings and in the statistical literature. One approach to avoiding the dichotomization associated with hypothesis testing is to provide distributions for parameters. A familiar distribution is the posterior density of Bayesian inference, but there are renewed efforts to provide something like probability statements for parameter while avoiding specification of a prior probability. I will discuss the strengths and limitations of these procedures, with special attention to so-called objective Bayesian approaches.


About ICML 2020

The International Conference on Machine Learning (ICML) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence known as machine learning. ICML is globally renowned for presenting and publishing cutting-edge research on all aspects of machine learning used in closely related areas like artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, and robotics. ICML is one of the fastest growing artificial intelligence conferences in the world. Participants at ICML span a wide range of backgrounds, from academic and industrial researchers, to entrepreneurs and engineers, to graduate students and postdocs.

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