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by Dennis V. Lindley
Understanding Uncertainty, Revised Edition
Cover
Wiley Series in Probability and Statistics
Title Page
Copyright
Preface
Prologue
Chapter 1: Uncertainty
1.1 Introduction
1.2 Examples
1.3 Suppression of Uncertainty
1.4 The Removal of Uncertainty
1.5 The Uses of Uncertainty
1.6 The Calculus of Uncertainty
1.7 Beliefs
1.8 Decision Analysis
Chapter 2: Stylistic Questions
2.1 Reason
2.2 Unreason
2.3 Facts
2.4 Emotion
2.5 Normative and Descriptive Approaches
2.6 Simplicity
2.7 Mathematics
2.8 Writing
2.9 Mathematics Tutorial
Chapter 3: Probability
3.1 Measurement
3.2 Randomness
3.3 A Standard for Probability
3.4 Probability
3.5 Coherence
3.6 Belief
3.7 Complementary Event
3.8 Odds
3.9 Knowledge Base
3.10 Examples
3.11 Retrospect
Chapter 4: Two Events
4.1 Two Events
4.2 Conditional Probability
4.3 Independence
4.4 Association
4.5 Examples
4.6 Supposition and Fact
4.7 Seeing and Doing
Chapter 5: The Rules of Probability
5.1 Combinations of Events
5.2 Addition Rule
5.3 Multiplication Rule
5.4 The Basic Rules
5.5 Examples
5.6 Extension of the Conversation
5.7 Dutch Books
5.8 Scoring Rules
5.9 Logic Again
5.10 Decision Analysis
5.11 The Prisoners' Dilemma
5.12 The Calculus and Reality
5.13 Closure
Chapter 6: Bayes Rule
6.1 Transposed Conditionals
6.2 Learning
6.3 Bayes Rule
6.4 Medical Diagnosis
6.5 Odds Form of Bayes Rule
6.6 Forensic Evidence
6.7 Likelihood Ratio
6.8 Cromwell's Rule
6.9 A Tale of two Urns
6.10 Ravens
6.11 Diagnosis and Related Matters
6.12 Information
Chapter 7: Measuring Uncertainty
7.1 Classical Form
7.2 Frequency Data
7.3 Exchangeability
7.4 Bernoulli Series
7.5 De Finetti's Result
7.6 Large Numbers
7.7 Belief and Frequency
7.8 Chance
Chapter 8: Three Events
8.1 The Rules of Probability
8.2 Simpson's Paradox
8.3 Source of the Paradox
8.4 Experimentation
8.5 Randomization
8.6 Exchangeability
8.7 Spurious Association
8.8 Independence
8.9 Conclusions
Chapter 9: Variation
9.1 Variation and Uncertainty
9.2 Binomial Distribution
9.3 Expectation
9.4 Poisson Distribution
9.5 Spread
9.6 Variability as an Experimental Tool
9.7 Probability and Chance
9.8 Pictorial Representation
9.9 Probability Densities
9.10 The Normal Distribution
9.11 Variation as a Natural Phenomenon
9.12 Ellsberg's Paradox
Chapter 10: Decision Analysis
10.1 Beliefs and Actions
10.2 Comparison of Consequences
10.3 Medical Example
10.4 Maximization of Expected Utility
10.5 More on Utility
10.6 Some Complications
10.7 Reason and Emotion
10.8 Numeracy
10.9 Expected Utility
10.10 Decision Trees
10.11 The Art and Science of Decision Analysis
10.12 Further Complications
10.13 Combination of Features
10.14 Legal Applications
Chapter 11: Science
11.1 Scientific Method
11.2 Science and Education
11.3 Data Uncertainty
11.4 Theories
11.5 Uncertainty of a Theory
11.6 The Bayesian Development
11.7 Modification of Theories
11.8 Models
11.9 Hypothesis Testing
11.10 Significance Tests
11.11 Repetition
11.12 Summary
Chapter 12: Examples
12.1 Introduction
12.2 CARDS
12.3 The Three Doors
12.4 The Problem of Two Daughters
12.5 Two More Daughters and Cardano
12.6 The two Envelopes
12.7 Y2K
12.8 UFOs
12.9 Conglomerability
12.10 Efron's Dice
Chapter 13: Probability Assessment
13.1 Nonrepeatable Events
13.2 Two Events
13.3 Coherence
13.4 Probabilistic Reasoning
13.5 Trickle Down
13.6 Summary
Chapter 14: Statistics
14.1 Bayesian Statistics
14.2 A Bayesian Example
14.3 Frequency Statistics
14.4 Significance Tests
14.5 Betting
14.6 Finance
Epilogue
Subject Index
Index of Examples
Index of Notations
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