In this note we’ll capture reflections about Jun Otsuka’s Thinking about statistics.

Statistical Models and the Problem of Induction

The book begins by framing the different epistemological projects of both #Bayesian and #Frequentist patterns of inference as approaches to solving the problem of induction expressed by David Hume.

This is a nice lens on the development of statistics and the applied work of statistical modelling. The two probabilistic frameworks are contrasted or compared to the more pragmatist position of model selection based on predictive power. We may prefer a model which does not capture the true data generating process just so long as it performs better in prediction tasks.