Philosophy of Statistics

IntroductionPhilosophy of Statistics: An Introduction, by Prasanta S. Bandyopadhyay and Malcolm R. ForsterPart I. Probability & StatisticsElementary Probability and Statistics: A Primer, by Prasanta S. Bandyopadhyay and Steve CherryPart II. Philosophical Controversies about Conditional ProbabilityConditional Probability, by Alan HájekThe Varieties of Conditional Probability, by Kenny EaswaranPart III. Four Paradigms of StatisticsClassical Statistics Paradigm Error Statistics, by Deborah G. Mayo and Aris SpanosSignificance Testing, by Michael Dickson and Davis BairdBayesian ParadigmThe Bayesian Decision-Theoretic Approach to Statistics, by Paul WeirichModern Bayesian Inference: Foundations and Objective Methods, by José M. BernardoEvidential Probability and Objective Bayesian Epistemology, by Gregory Wheeler and Jon WilliamsonConfirmation Theory, by James HawthorneChallenges to Bayesian Confirmation Theory, by John D. NortonBayesianism as a Pure Logic of Inference, by Colin HowsonBayesian Inductive Logic, Verisimilitude, and Statistics, by Roberto FestaLikelihood ParadigmLikelihood and its Evidential Framework, by Jeffrey D. BlumeEvidence, Evidence Functions, and Error Probabilities, by Mark L. Taper and Subhash R. LeleAkaikean ParadigmAIC Scores as Evidence — a Bayesian Interpretation, by Malcolm Forster and Elliott SoberPart IV: The Likelihood PrincipleThe Likelihood Principle, by Jason GrossmanPart V: Recent Advances in Model SelectionAIC, BIC and Recent Advances in Model Selection, by Arijit Chakrabarti and Jayanta K. GhoshPosterior Model Probabilities, by A. Philip DawidPart VI: Attempts to Understand Different Aspects of “Randomness”Defining Randomness, by Deborah BennettMathematical Foundations of Randomness, by Abhijit DasguptaPart VII: Probabilistic and Statistical ParadoxesParadoxes of Probability, by Susan VinebergStatistical Paradoxes: Take It to The Limit, by C. Andy TsaoPart VIII: Statistics and Inductive InferenceStatistics as Inductive Inference, by Jan-Willem RomeijnPart IX: Various Issues about Causal InferenceCommon Cause in Causal Inference, by Peter SpirtesThe Logic and Philosophy of Causal Inference: A Statistical Perspective, by Sander GreenlandPart X: Some Philosophical Issues Concerning Statistical Learning TheoryStatistical Learning Theory as a Framework for the Philosophy of Induction, by Gilbert Harman and Sanjeev KulkarniTestability and Statistical Learning Theory, by Daniel SteelPart XI: Different Approaches to Simplicity Related to Inference and TruthLuckiness and Regret in Minimum Description Length Inference, by Steven de Rooij and Peter D. GrünwaldMML, Hybrid Bayesian Network Graphical Models, Statistical, by Consistency, Invariance and Uniqueness, by David L. DoweSimplicity, Truth and Probability, by Kevin T. KellyPart XII: Special Problems in Statistics/Computer ScienceNormal Approximations, by Robert J. BoikStein’s Phenomenon, by Richard Charnigo and Cidambi SrinivasanData, Data, Everywhere: Statistical Issues in Data Mining, by Choh Man TengPart XIII: An Application of Statistics to Climate ChangeAn Application of Statistics in Climate Change: Detection of Nonlinear Changes in a Streamflow Timing Measure in the Columbia and Missouri Headwaters, by Mark C. Greenwood, Joel Harper and Johnnie MoorePart XIV: Historical Approaches to Probability/StatisticsThe Subjective and the Objective, by Sandy L. ZabellProbability in Ancient India, by C. K. Raju