Inference and Intervention by Ryall, Michael D. -- Read -- Imperial Library of Trantor

Index

Cover Half Title Title Page Copyright Page Table of Contents List of figures Acknowledgments 1 Introduction to Causal Analysis

1.1 Situational Assessment 1.2 Managerial Intervention

2 Qualitative Causal Models

2.1 Setting the Stage 2.2 Building a Qualitative Causal Model

2.2.1 Nodes 2.2.2 Links 2.2.3 Some Examples of Qualitative Causal Models

2.3 Causal Independence

2.3.1 Serial Triplets 2.3.2 Diverging Triplets 2.3.3 Converging Triplets 2.3.4 Causal Independence in General

3 Application: Interview Case Study

3.1 Getting Started 3.2 Focus on the Significant Drivers 3.3 Seek Sources of Common Problems 3.4 Ask Specific Questions

3.4.1 Administrative Staff 3.4.2 Service Staff 3.4.3 Doctors: Generalists and Specialists

3.5 Bring it All Together 3.6 Provide Specific Recommendations

3.6.1 Upgrade Account Management System 3.6.2 Adjust to an Aging Population 3.6.3 Appeal to a Younger Crowd 3.6.4 Final Note

4 Quantitative Causal Models

4. Probability Basics

4.1.1 Variable States 4.1.2 Events 4.1.3 Probabilities 4.1.4 Conditional Probabilities 4.1.5 Joint Probabilities 4.1.6 System States 4.1.7 Bayes' Rule

4.2 Quantifying a Qualitative Model

4.2.1 More Refined Approximations

4.3 Working with Quantitative Models

4.3.1 Probabilities from Count Data 4.3.2 Joint Probability Tables 4.3.3 The Complete Advertising Model 4.3.4 System-Level Joint Distribution & Factorization 4.3.5 Marginalization

4.4 The Move to Causal Models

5 Situational Analysis

5.1 Marginal from Conditional Probabilities

5.1.1 Serial Connections 5.1.2 Diverging Connections 5.1.3 Converging Connections

5.2 Evidence & Inference in Causal Models

5.2.1 Serial Connection 5.2.2 Divergent Connection 5.2.3 Convergent Connection

6 Application: Modeling Business Financials

6.1 The Spreadsheet Approach 6.2 Building a Causal Model 6.3 Marketing Uses the “Prosecutor's Fallacy” 6.4 Green Ink Creates Simpson's Paradox

7 Single-Agent Interventions

7.1 One Decision, No Information 7.2 Multiple Decisions with Information

7.2.1 The Extended Model 7.2.2 General Solution Procedure

8 Application: Disrupting the Taxi Business

8.1 An Allocation of Resources Decision 8.2 Price Uncertainty and Market Research 8.3 Competitor Legal Response

9 Multi-Agent Interventions

9.1 Elements of a Game 9.2 Nash Solutions 9.3 Causal Form Games 9.4 Solving Games with Causal Models

9.4.1 Vicious Incumbent Entry Game

9.5 Games with Non-Trivial Strategies

9.5.1 Setup for the model 9.5.2 Solving the Reformulated Model 9.5.3 Insights from Technology Development Problem

9.6 Software Solutions

10 Data-Driven Causal Modeling

10.1 Causality versus Probability

10.1.1 Probability View 10.1.2 Causality View

10.2 Observational Indistinguishability

10.2.1 The Observational Indistinguishability Theorem 10.2.2 Causal Identification

10.3 Building Predictive Regression Models

10.3.1 From Structural Equation to Causal Models 10.3.2 Linear Regressions and Causal Models 10.3.3 Good Causal Models Imply Good Predictions 10.3.4 A Brief Note on Box Office Gross

Bibliography Index

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