Book description
Decision theory provides a formal framework for making logical choices in the face of uncertainty. Given a set of alternatives, a set of consequences, and a correspondence between those sets, decision theory offers conceptually simple procedures for choice. This book presents an overview of the fundamental concepts and outcomes of rational decision making under uncertainty, highlighting the implications for statistical practice.The authors have developed a series of self contained chapters focusing on bridging the gaps between the different fields that have contributed to rational decision making and presenting ideas in a unified framework and notation while respecting and highlighting the different and sometimes conflicting perspectives.
This book:
 Provides a rich collection of techniques and procedures.
 Discusses the foundational aspects and modern day practice.
 Links foundations to practical applications in biostatistics, computer science, engineering and economics.
 Presents different perspectives and controversies to encourage readers to form their own opinion of decision making and statistics.
Decision Theory is fundamental to all scientific disciplines, including biostatistics, computer science, economics and engineering. Anyone interested in the whys and wherefores of statistical science will find much to enjoy in this book.
Table of contents
 Cover Page
 Title Page
 Copyright Page
 Contents
 Preface
 Acknowledgments
 Chapter 1: Introduction

Part One: Foundations
 Chapter 2: Coherence
 Chapter 3: Utility
 Chapter 4: Utility in action
 Chapter 5: Ramsey and Savage
 Chapter 6: State independence

Part Two: Statistical Decision Theory
 Chapter 7: Decision functions
 Chapter 8: Admissibility
 Chapter 9: Shrinkage
 Chapter 10: Scoring rules
 Chapter 11: Choosing models

Part Three: Optimal Design
 Chapter 12: Dynamic programming
 Chapter 13: Changes in utility as information
 Chapter 14: Sample size
 Chapter 15: Stopping
 Appendix
 References
 Index
 Wiley Series in Probability and Statistics
Product information
 Title: Decision Theory
 Author(s):
 Release date: May 2009
 Publisher(s): Wiley
 ISBN: 9780471496571
You might also like
book
HandsOn Machine Learning with ScikitLearn, Keras, and TensorFlow, 2nd Edition
Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. …
book
Introduction to Probability
Developed from celebrated Harvard statistics lectures, Introduction to Probability provides essential language and tools for understanding …
book
40 Algorithms Every Programmer Should Know
Learn algorithms for solving classic computer science problems with this concise guide covering everything from fundamental …
book
Data Science from Scratch, 2nd Edition
To really learn data science, you should not only master the tools—data science libraries, frameworks, modules, …