This book presents an alternative for traditional null hypothesis testing. It builds on the idea that researchers usually have more informative research-questions than the "nothing is going on" null hypothesis, or the "something is going on" alternative hypothesis. To be more precise, researchers often express their expectations in terms of expected orderings in parameters, for instance, in group means. This book introduces a novel approach, wherein theories or expectations of empirical researchers are translated into one or more so-called informative hypotheses, i.e., hypotheses imposing inequality constraints on (some of) the model parameters. As a consequence, informative hypotheses are much closer to the actual questions researchers have and therefore make optimal use of the data to provide more informative answers to these questions.

"This book provides the philosophical, statistical and psychological foundation for the evaluation of informed hypotheses."

An Introduction to Bayesian Evaluation of Informative Hypotheses.- An Introduction to Bayesian Evaluation of Informative Hypotheses.- Bayesian Evaluation of Informative Hypotheses.- Illustrative Psychological Data and Hypotheses for Bayesian Inequality Constrained Analysis of Variance.- Bayesian Estimation for Inequality Constrained Analysis of Variance.- Encompassing Prior Based Model Selection for Inequality Constrained Analysis of Variance.- An Evaluation of Bayesian Inequality Constrained Analysis of Variance.- A Further Study of Prior Distributions and the Bayes Factor.- Bayes Factors Based on Test Statistics Under Order Restrictions.- Objective Bayes Factors for Informative Hypotheses: "Completing" the Informative Hypothesis and "Splitting" the Bayes Factors.- The Bayes Factor Versus Other Model Selection Criteria for the Selection of Constrained Models.- Bayesian Versus Frequentist Inference.- Beyond Analysis of Variance.- Inequality Constrained Analysis of Covariance.- Inequality Constrained Latent Class Models.- Inequality Constrained Contingency Table Analysis.- Inequality Constrained Multilevel Models.- Evaluations.- A Psychologist's View on Bayesian Evaluation of Informative Hypotheses.- A Statistician's View on Bayesian Evaluation of Informative Hypotheses.- A Philosopher's View on Bayesian Evaluation of Informative Hypotheses.