Toward a Bayesian Decision-Theoretic 1 Running Head: BAYESIAN DECISION-THEORETIC APPROACH Toward a Bayesian Decision-Theoretic Approach to Hypothesis-Testing in Psychology

Toward a Bayesian Decision-Theoretic 2 The testing of null hypotheses is a methodologically limited way to making decisions in psychology and science more generally. Null hypothesis significance testing, or “NHST,” has undergone severe criticism since its inception with R.A. Fisher in early 20 th century. The mere fact that the probability of some data is less than some conventional cut-off (e.g.,.05) should not by itself suggest the rejection of the null and the adoption of some hypothesized alternative. What is missing from the conventional hypothesis-testing paradigm is the incorporation of actual or estimated losses and costs that result from the possibilities of making erroneous decisions when choosing between H0 and H1. In this article, the problems with NHST are briefly reviewed, followed by a presentation of the Bayesian decision-theoretic approach to hypothesis testing popularized by such decision theorists as Berger (1993) and Winkler (2002). The approach incorporates estimates of the actual losses incurred in the decision-making process, and is recommended for use in psychology and related sciences. Simple illustrations of the approach are given