Abstract: Nearly everyone is dissatisfied with classical statistical hypothesis testing approaches to comparing things. In this talk, a Bayesian method is described that uses model resampling statistics to make direct comparisons between models (i.e. no p-values). An example is shown to illustrate how to determine practical (!= statistical) differences in performance using the tidyposterior R package.
Bio: Max Kuhn works at RStudio developing software for data analysis and modeling. He previously worked in pharmaceutical and molecular diagnostic research for more than 18 years. Max’s interests are in predictive modeling and machine learning and is the author of six R packages, including the [caret package](http://topepo.github.io/caret/). He and Kjell Johnson published the bestselling book [Applied Predictive Modeling (http://appliedpredictivemodeling.com) in 2013. Max holds a B.S. in Mathematics and a Ph.D. in Biostatistics.
Max Kuhn, PhD
Core Contributor of R and Software Engineer at RStudio