Testing by Betting: A Strategy for Statistical and Scientific Communication
Glenn Shafer
2021Journal of the Royal Statistical Society Series A (Statistics in Society)113 citationsDOIOpen Access PDF
Abstract
Abstract The most widely used concept of statistical inference—the p-value—is too complicated for effective communication to a wide audience. This paper introduces a simpler way of reporting statistical evidence: report the outcome of a bet against the null hypothesis. This leads to a new role for likelihood, to alternatives to power and confidence, and to a framework for meta-analysis that accommodates both planned and opportunistic testing of statistical hypotheses and probabilistic forecasts. This framework builds on the foundation for mathematical probability developed in previous work by Vladimir Vovk and myself.
Topics & Concepts
Statistical hypothesis testingStatistical inferenceNull hypothesisProbabilistic logicStatistical powerInferencep-valueOutcome (game theory)Computer scienceStatistical modelFoundation (evidence)Null (SQL)EconometricsStatisticsArtificial intelligenceData miningMathematicsMathematical economicsGeographyArchaeologyGaussian Processes and Bayesian InferenceStatistical Methods and InferenceStatistical Methods in Clinical Trials