Proceedings of the Annual Meeting of the Cognitive Science Society

In view of the ongoing replication crisis and various frustrations about classical null-hypothesis significance testing, calls for a statistical reform have increased. Often, it has been argued that the Bayesian approach offers a promising alternative to classical statistics, but at the same time, both approaches are sometimes hard to compare. This paper offers some basic steps for establishing a more decisive common ground and take steps towards resolving some fundamental conceptual issues, by introducing the frameworks of epistemic accuracy and efficient experimentation. Efficiency (i.e. the ratio between the accuracy of conclusions, and the experimental resources needed) is of central importance to good scientific inquiry. This paper shows how considerations of efficiency and accuracy motivate a broadly Bayesian approach, which however can also make room for frequentist tenets, and thereby push us towards a more unified and powerful framework for scientific inference.