Philosophy of Statistics

Dov M. Gabbay, Paul Thagard, John Woods

• Publisher: North Holland
• Year: 2011
• Print ISBN: 9780444518620
• eBook ISBN: 9780080930961
• Topic: Philosophy
• Subtopic: Probability & Statistics

Statisticians and philosophers of science have many common interests but restricted communication with each other. This volume aims to remedy these shortcomings. It provides state-of-the-art research in the area of philosophy of statistics by encouraging numerous experts to communicate with one another without feeling "restricted by their disciplines or thinking "piecemeal in their treatment of issues.A second goal of this book is to present work in the field without bias toward any particular statistical paradigm.Broadly speaking, the essays in this Handbook are concerned with problems of induction, statistics and probability. For centuries, foundational problems like induction have been among philosophers' favorite topics; recently, however, non-philosophers have increasingly taken a keen interest in these issues. This volume accordingly contains papers by both philosophers and non-philosophers, including scholars from nine academic disciplines.- Provides a bridge between philosophy and current scientific findings- Covers theory and applications- Encourages multi-disciplinary dialogue

Index

0-9, and Symbols

1-, 2-, n-random, see randomness

A

A-recursion

461

a posteriori

901

abbreviation

955

Abhandlunguen de Fries'schen Schule

1159n

Abramovich, F.

602

absolutely normal

658

acceptability

474

acceptance rules

475

acceptance-based inference

474, 475, 484

accommodates

984

accuracy

987, 991-993, 997

accurate prediction

991, 997

Achinstein, P.

420

acronym

955

action

268, 269

acyclic linear causal model, 1011n ad hoc

984

ad hoc hypothesis

395

ad hoc grammar

868

Adams' thesis

127

Adams's principle

465

Adams, E. W.

127, 128, 131, 465

addition rule

80

additive mixed models

1131, 1132, 1138, 1142

additivity

406

adjunction

1108

adjustable

989

adjustable parameters

984, 988

adjusted

989

admissibility

292

admissible

1008

advantage

299

advantage of rejecting

299

AFL

921, 922

AIC

2, 3, 16, 17, 18, 24, 25, 43, 45, 110, 426, 535, 541, 545, 583, 584-586, 588-590, 592-594, 598-600, 602, 603, 889, 896, 932-934, 946, 994, 996, 1131, 1132, 1135-1138

Airy, G.

1162n

Akaike, H.

535, 541, 583, 592, 593

A...

Table of contents

• Cover Image
• Table of Contents
• Front matter
• Copyright
• Dedication
• General Preface
• Preface
• Contributors
• Philosophy of Statistics
• Elementary Probability and Statistics
• Conditional Probability
• The Varieties of Conditional Probability
• Error Statistics
• Significance Testing
• The Bayesian Decision-Theoretic Approach to Statistics
• Modern Bayesian Inference
• Evidential Probability and Objective Bayesian Epistemology
• Confirmation 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
• 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
• Statistics as Inductive Inference
• Common Cause In Causal Inference
• The Logic and Philosophy of Causal Inference
• Statistical Learning Theory as a Framework for the Philosophy of Induction
• Testability and Statistical Learning Theory
• Luckiness and Regret in Minimum Description Length Inference
• MML, Hybrid Bayesian Network Graphical Models, Statistical Consistency, Invariance and Uniqueness
• Simplicity, Truth, and Probability
• Normal Approximations
• Stein's Phenomenon
• Data, Data, Everywhere
• An Application of Statistics in Climate Change
• The Subjective and the Objective
• Probability in Ancient India
• Index