Comparing Models using Resampling and Bayesian Methods
Comparing Models using Resampling and Bayesian Methods


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.


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]( He and Kjell Johnson published the bestselling book [Applied Predictive Modeling ( in 2013. Max holds a B.S. in Mathematics and a Ph.D. in Biostatistics.

Open Data Science




Open Data Science
One Broadway
Cambridge, MA 02142

Privacy Settings
We use cookies to enhance your experience while using our website. If you are using our Services via a browser you can restrict, block or remove cookies through your web browser settings. We also use content and scripts from third parties that may use tracking technologies. You can selectively provide your consent below to allow such third party embeds. For complete information about the cookies we use, data we collect and how we process them, please check our Privacy Policy
Consent to display content from Youtube
Consent to display content from Vimeo
Google Maps
Consent to display content from Google