Six Statistical Senses

TL;DR

This paper introduces six fundamental 'statistical senses' as categories that encapsulate key ideas, aiming to enhance understanding and integration of statistical theory, methods, and computation for better statistical reasoning.

Contribution

It proposes a novel categorization of statistical concepts into six senses to foster deeper insight and connections within statistical thinking and practice.

Findings

Provides a conceptual framework linking statistical ideas

Illustrates each sense with relevant principles and methods

Aims to build statistical phronesis for data science

Abstract

This article proposes a set of categories, each one representing a particular distillation of important statistical ideas. Each category is labeled a "sense" because we think of these as essential in helping every statistical mind connect in constructive and insightful ways with statistical theory, methodologies, and computation, toward the ultimate goal of building statistical phronesis. The illustration of each sense with statistical principles and methods provides a sensical tour of the conceptual landscape of statistics, as a leading discipline in the data science ecosystem.