The following is an email exchange with Hyunseung Kang on the nature of randomization inference. This was sparked by a couple of papers by David Freedman and David Lane: A Nonstochastic Interpretation of Reported Significance Levels; Significance Testing in a Nonstochastic Setting.

This post is derived from my talk “Fisher, Statistics, and Randomization” in the Fisher in the 21st Century Conference organized by Fisher’s College, Gonville & Caius. In the first half of that talk, I tried to trace the origin of randomization.

I read a few interesting articles this week on the Fisher-Neyman debate on the foundation of hypothesis testing:
The Fisher, Neyman-Pearson Theories of Testing Hypotheses: One Theory or Two?. Rigorous uncertainty: why RA Fisher is important.

Over this Easter weekend, I wrote the following commentary for the reprinting on Leo Breiman’s paper “Statistical Modeling: The Two Cultures” by Observational Studies. This is partly based on a talk I gave last year.

2024

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