Excerpt from A Fortiori Bayesian Inference in Psychological Research Bayes Law, or the law of conditional probability, provides a natural inference framework for one who views hypothesis testing as parameter estimation. Heretofore a major difficul ty in applying Bayesian ideas to psychological contexts has been the specification of an objective or public prior. This paper proposes a rule for selecting a prior hypothesis which is both unambiguous and hostile to the research hypothesis: choose the prior so that 1) its expectation is the conventional null value and 2) it has maximum probability of producing the obser ved data. The rule is employed to develop a complete set of tests for nominal data, and both a one-sample and a two-sample. About the Publisher Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.