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9781108421645

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Social Inquiry and Bayesian Inference outlines the philosophy, logic, and mathematics of Bayesian process tracing more thoroughly than any other source to date, and it translates them into practical advice that qualitative researchers can carry out even if they don't want to wade through the details of the math. This will be the seminal statement on Bayesian process tracing for many years to come. It should be on the syllabus of everyone teaching case study methods and the bookshelf of everyone using these methods in their own research. Andrew Bennett, Professor of International Relations, Georgetown University 'Fairfield and Charman have written a major book that will resonate across the social sciences. They manage to combine astute technical discussion of the Bayesian approach with a 'how to' that will assist researchers regardless of approach or prior experience with these tools.' Stephan Haggard, Lawrence and Sallye Krause Distinguished Professor, School of Global Policy and Strategy, University of California San Diego In this book, Fairfield and Charman develop the most systematic and concrete approach to qualitative research in political science. The Bayesian framework provides a clear structure for learning from evidence within and across cases, and the book provides clear and actionable guidelines that scholars can take on board. Readers will learn a great deal from this book about designing and carrying out rigorous and transparent qualitative research. Hillel David Soifer, Associate Professor, Department of Political Science, Temple University 'This book sets out a powerful set of tools for undertaking systematic and analytically explicit qualitative inference. Fairfield and Charman provide a clear and accessible introduction to Bayesian principles and show how they can be applied to the kinds of questions and data with which qualitative social scientists routinely grapple. This volume represents an important step forward for the development and teaching of qualitative methods.' Alan Jacobs, Professor of Political Science, University of British Columbia

Social Inquiry and Bayesian Inference outlines the philosophy, logic, and mathematics of Bayesian process tracing more thoroughly than any other source to date, and it translates them into practical advice that qualitative researchers can carry out even if they don't want to wade through the details of the math. This will be the seminal statement on Bayesian process tracing for many years to come. It should be on the syllabus of everyone teaching case study methods and the bookshelf of everyone using these methods in their own research. Andrew Bennett, Professor of International Relations, Georgetown University Fairfield and Charman have written a major book that will resonate across the social sciences. They manage to combine astute technical discussion of the Bayesian approach with a how to that will assist researchers regardless of approach or prior experience with these tools. Stephan Haggard, Lawrence and Sallye Krause Distinguished Professor, School of Global Policy and Strategy, University of California San Diego In this book, Fairfield and Charman develop the most systematic and concrete approach to qualitative research in political science. The Bayesian framework provides a clear structure for learning from evidence within and across cases, and the book provides clear and actionable guidelines that scholars can take on board. Readers will learn a great deal from this book about designing and carrying out rigorous and transparent qualitative research. Hillel David Soifer, Associate Professor, Department of Political Science, Temple University

Author Information

Tasha Fairfield is an Associate Professor at the London School of Economics, with a Ph.D in political science from the University of California, Berkeley, and an M.S. in physics from Stanford University. Her publications include Private Wealth and Public Revenue in Latin America (Cambridge, 2015), which won the Donna Lee Van Cott Book Award. Andrew E. Charman is a Lecturer and Researcher in Physics at the University of California, Berkeley, and an expert in Bayesian statistics. Beyond analyzing measurements of antimatter and the foundations of quantum mechanics, he has explored methods for optimal congressional apportionment and statistical mechanical models of gerrymandering. His previous work with Tasha Fairfield received APSA's QMMR Sage Paper Award.

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