Nonprobabilistic Statistical Inference:

A Set-Theoretic Approach

 

HENRY ROUANET, JEAN-MARC BERNARD, and BRUNO LECOUTRE

The American Statistician, 40, 60-65

Summary

 

The familiar sampling procedures of statistical inference can be recast within a purely set-theoretic (ST) framework, without resorting to probabilistic prerequisites. This article is an introduction to the ST approach of statistical inference, with emphasis on its attractiveness for teaching. The main points treated are unsophisticated ST significance testing and ST inference for a relative frequency (proportion).