Signs of obsolescence in psychological statistics: Significance versus contemporary theory

Abstract

Contemporary statistical theory has moved away in its balance from the emphasis on significance levels and hypothesis testing that is built into many computer packages familiar to, and obviously created for, psychologists. Serious fundamental criticisms have been raised by statisticians about the tradition of inference associated with Neyman, which he himself had found convincing half a century ago, and which often is still the only theory found in textbooks of statistics-for-psychologists. A resurgence of interest in Bayesian inference, and the solution of associated computational problems, has made available methods and data interpretations that are still not widely known or taught in psychology departments. An elementary example to distinguish between “significance” levels, likelihoods, and informational content is offered.