Measuring Statistical Evidence: A Short Report

TL;DR

This paper discusses the concept of statistical evidence, critiques existing methods, and advocates for the Relative Belief Ratio as a principled approach to measure evidence in statistical inference.

Contribution

It provides a conceptual overview of evidential statistics and introduces the Relative Belief Ratio as a novel, well-motivated method for measuring statistical evidence.

Findings

Critiques of current evidence measurement methods

Introduction of the Relative Belief Ratio as a primary measure

Emphasis on principles for ideal inference methods

Abstract

This short text tried to establish a big picture of what evidential statistics is about and how an ideal inference method should behave. Moreover, by examining shortcomings of some of the currently used methods for measuring evidence and utilizing some intuitive principles, we motivated the Relative Belief Ratio as the primary method of characterizing statistical evidence. Number of topics has been omitted for the interest of this text and the reader is strongly advised to refer to (Evans, 2015) as the primary source for further readings of the subject.