Philosophy of Statistics

Elementary Probability and Statistics: A Primer Conditional Probability, by Alan HájekThe Varieties of Conditional Probability Paradigm Error Statistics Significance Testing The Bayesian Decision-Theoretic Approach to Statistics Modern Bayesian Inference: Foundations and Objective Methods Evidential Probability and Objective Bayesian EpistemologyConfirmation Theory Challenges to Bayesian Confirmation Theory Bayesianism as a Pure Logic of Inference Bayesian Inductive Logic, Verisimilitude, and Statistics Likelihood and its Evidential Framework Evidence, Evidence Functions, and Error Probabilities AIC Scores as Evidence - a Bayesian Interpretation The Likelihood Principle AIC, BIC and Recent Advances in Model Selection Posterior Model Probabilities Defining Randomness Mathematical Foundations of Randomness Paradoxes of Probability Statistical Paradoxes: Take It to The Limit Statistics as Inductive Inference Common Cause in Causal Inference The Logic and Philosophy of Causal Inference: A Statistical Perspective Statistical Learning Theory as a Framework for the Philosophy of Induction Testability and Statistical Learning Theory Luckiness and Regret in Minimum Description Length InferenceMML, Hybrid Bayesian Network Graphical Models, Statistical, by Consistency, Invariance and Uniqueness Simplicity, Truth and Probability Normal Approximations Stein's Phenomenon Data, Data, Everywhere: Statistical Issues in Data Mining An Application of Statistics in Climate Change: Detection of Nonlinear Changes in a Streamflow Timing Measure in the Columbia and Missouri Headwaters The Subjective and the Objective Probability in Ancient India

Dov M. Gabbay is Augustus De Morgan Professor Emeritus of Logic at the Group of Logic, Language and Computation, Department of Computer Science, King's College London. He has authored over four hundred and fifty research papers and over thirty research monographs. He is editor of several international Journals, and many reference works and Handbooks of Logic.