Comparative Statistical Inference, Third Edition

This fully updated and revised third edition, presents a wide ranging, balanced account of the fundamental issues across the full spectrum of inference and decision-making. Much has happened in this field since the second edition was published: for example, Bayesian inferential procedures have not only gained acceptance but are often the preferred methodology. This book will be welcomed by both the student and practising statistician wishing to study at a fairly elementary level, the basic conceptual and interpretative distinctions between the different approaches, how they interrelate, what assumptions they are based on, and the practical implications of such distinctions. As in earlier editions, the material is set in a historical context to more powerfully illustrate the ideas and concepts. \* Includes fully updated and revised material from the successful second edition \* Recent changes in emphasis, principle and methodology are carefully explained and evaluated \* Discusses all recent major developments \* Particular attention is given to the nature and importance of basic concepts (probability, utility, likelihood etc) \* Includes extensive references and bibliography Written by a well-known and respected author, the essence of this successful book remains unchanged providing the reader with a thorough explanation of the many approaches to inference and decision making.Content: Chapter 1 Introduction: Statistical Inference and Decision?Making (pages 1–27): Chapter 2 An Illustration of the Different Approaches (pages 29–63): Chapter 3 Probability (pages 65–98): Chapter 4 Utility and Decision?Making (pages 99–121): Chapter 5 Classical Inference (pages 123–200): Chapter 6 Bayesian Inference (pages 101–249): Chapter 7 Decision Theory (pages 251–295): Chapter 8 Other Approaches (pages 297–329): Chapter 9 Perspective (pages 331–336): This Fully Updated And Revised Third Edition, Presents A Wide Ranging, Balanced Account Of The Fundamental Issues Across The Full Spectrum Of Inference And Decision-making. Much Has Happened In This Field Since The Second Edition Was Published: For Example, Bayesian Inferential Procedures Have Not Only Gained Acceptance But Are Often The Preferred Methodology. This Book Will Be Welcomed By Both The Student And Practising Statistician Wishing To Study At A Fairly Elementary Level, The Basic Conceptual And Interpretative Distinctions Between The Different Approaches, How They Interrelate, What Assumptions They Are Based On, And The Practical Implications Of Such Distinctions. As In Earlier Editions, The Material Is Set In A Historical Context To More Powerfully Illustrate The Ideas And Concepts. * Includes Fully Updated And Revised Material From The Successful Second Edition * Recent Changes In Emphasis, Principle And Methodology Are Carefully Explained And Evaluated * Discusses All Recent Major Developments * Particular Attention Is Given To The Nature And Importance Of Basic Concepts (probability, Utility, Likelihood Etc) * Includes Extensive References And Bibliography Written By A Well-known And Respected Author, The Essence Of This Successful Book Remains Unchanged Providing The Reader With A Thorough Explanation Of The Many Approaches To Inference And Decision Making--publisher Description. Introduction: Statistical Inference And Decision-making -- An Illustration Of The Different Approaches -- Probability -- Utility And Decision-making -- Classical Inference -- Bayesian Inference -- Decision Theory -- Other Approaches. Vic Barnett. Includes Bibliographical References (p. [337]-364) And Index. "This fully updated and revised third edition, presents a wide ranging, balanced account of the fundamental issues across the full spectrum of inference and decision-making. Much has happened in this field since the second edition was published: for example, Bayesian inferential procedures have not only gained acceptance but are often the preferred methodology. This book will be welcomed by both the student and practising statistician wishing to study at a fairly elementary level, the basic conceptual and interpretative distinctions between the different approaches, how they interrelate, what assumptions they are based on, and the practical implications of such distinctions. As in earlier editions, the material is set in a historical context to more powerfully illustrate the ideas and concepts. * Includes fully updated and revised material from the successful second edition * Recent changes in emphasis, principle and methodology are carefully explained and evaluated * Discusses all recent major developments * Particular attention is given to the nature and importance of basic concepts (probability, utility, likelihood etc) * Includes extensive references and bibliography Written by a well-known and respected author, the essence of this successful book remains unchanged providing the reader with a thorough explanation of the many approaches to inference and decision making" -- Provided by publisher « This fully updated and revised third edition, presents a wide ranging, balanced account of the fundamental issues across the full spectrum of inference and decision-making. Much has happened in this field since the second edition was published: for example, Bayesian inferential procedures have not only gained acceptance but are often the preferred methodology. This book will be welcomed by both the student and practising statistician wishing to study at a fairly elementary level, the basic conceptual and interpretative distinctions between the different approaches, how they interrelate, what assumptions they are based on, and the practical implications of such distinctions. As in earlier editions, the material is set in a historical context to more powerfully illustrate the ideas and concepts. Includes fully updated and revised material from the successful second edition Recent changes in emphasis, principle and methodology are carefully explained and evaluated Discusses all recent major developments Particular attention is given to the nature and importance of basic concepts (probability, utility, likelihood etc) Includes extensive references and bibliography Written by a well-known and respected author, the essence of this successful book remains unchanged providing the reader with a thorough explanation of the many approaches to inference and decision making. »-- Résumé de l'éditeur Provides a general, cross-sectional view of statistical inference and decision-making. Constructs a rational, composite theory for the way individuals react, or should react, stressing interrelationships and conceptual conflicts. Traces the range of different definitions and interpretations of the probability concepts which underlie different approaches to statistical inference and decision-making. Outlines utility theory and its implications for general decision-making. Discusses the Neyman-Pearson approach, Bayesian methods, and Decision Theory. Pays particular attention to the basic concepts of probability, utility, likelihood, sufficiency, conjugacy, and admissibility, both within and between the different approaches. -- Provided by publisher