ABSTRACT

Ryall and Bramson's Inference and Intervention is the first textbook on causal modeling with Bayesian networks for business applications. In a world of resource scarcity, a decision about which business elements to control or change – as the authors put it, a managerial intervention – must precede any decision on how to control or change them, and understanding causality is crucial to making effective interventions.

The authors cover the full spectrum of causal modeling techniques useful for the managerial role, whether for intervention, situational assessment, strategic decision-making, or forecasting. From the basic concepts and nomenclature of causal modeling to decision tree analysis, qualitative methods, and quantitative modeling tools, this book offers a toolbox for MBA students and business professionals to make successful decisions in a managerial setting.

chapter 1|13 pages

Introduction to Causal Analysis

chapter 2|30 pages

Qualitative Causal Models

chapter 3|34 pages

Application

Interview Case Study

chapter 4|31 pages

Quantitative Causal Models

chapter 5|23 pages

Situational Analysis

chapter 6|19 pages

Application

Modeling Business Financials

chapter 7|25 pages

Single-Agent Interventions

chapter 8|13 pages

Application

Disrupting the Taxi Business

chapter 9|35 pages

Multi-Agent Interventions

chapter 10|31 pages

Data-Driven Causal Modeling