Thinking Clearly with Data: A Guide to Quantitative Reasoning and Analysis
Princeton University Press. (Joint with Anthony Fowler).

You can access teaching resources (lecture notes, in class activities, exercise solutions, downloadable data) here

We found a small number of minor errors, here are the errata

An introduction to data science or statistics shouldn’t involve proving complex theorems or memorizing obscure terms and formulas, but that is exactly what most introductory quantitative textbooks emphasize. In contrast, Thinking Clearly with Data focuses, first and foremost, on critical thinking and conceptual understanding in order to teach students how to be better consumers and analysts of the kinds of quantitative information and arguments that they will encounter throughout their lives.

Among much else, the book teaches how to assess whether an observed relationship in data reflects a genuine relationship in the world and, if so, whether it is causal; how to make the most informative comparisons for answering questions; what questions to ask others who are making arguments using quantitative evidence; which statistics are particularly informative or misleading; how quantitative evidence should and shouldn’t influence decision-making; and how to make better decisions by using moral values as well as data. Filled with real-world examples, the book shows how its thinking tools apply to problems in a wide variety of subjects, including elections, civil conflict, crime, terrorism, financial crises, health care, sports, music, and space travel.

Above all else, Thinking Clearly with Data demonstrates why, despite the many benefits of our data-driven age, data can never be a substitute for thinking.

  • An ideal textbook for introductory quantitative methods courses in data science, statistics, political science, economics, psychology, sociology, public policy, and other fields
  • Introduces the basic toolkit of data analysis—including sampling, hypothesis testing, Bayesian inference, regression, experiments, instrumental variables, differences in differences, and regression discontinuity
  • Uses real-world examples and data from a wide variety of subjects
  • Includes practice questions and data exercises



Theory and Credibility. Princeton University Press. (Joint with Scott Ashworth and Christopher Berry).

Here are some slides I used to talk about Part I of the book at the 2021 EITM Summer Institute.


The credibility revolution, with its emphasis on empirical methods for causal inference, has led to concerns among scholars that the canonical questions about politics and society are being neglected because they are no longer deemed answerable. Theory and Credibility stakes out an opposing view—presenting a new vision of how, working together, the credibility revolution and formal theory can advance social scientific inquiry.

This book covers the conceptual foundations and practicalities of both model building and research design, providing a new framework to link theory and empirics. Drawing on diverse examples, it presents a typology of the rich set of interactions that are possible between theory and empirics. This typology opens up new ways for scholars to make progress on substantive questions, and enables researchers from disparate traditions to gain a deeper appreciation for each other’s work and why it matters.

Theory and Credibility shows theorists how to create models that are genuinely useful to empirical inquiry, and helps empiricists better understand how to structure their research in ways that speak to theoretically meaningful questions.





Political Economy for Public Policy. Princeton University Press. 2016.

Lecture notes, classroom activities, and other material that may be of interest to instructors can be found here.



This textbook uses modern political economy to introduce students of political science, government, economics, and public policy to the politics of the policymaking process. The book’s distinct political economy approach has two virtues. By developing general principles for thinking about policymaking, it can be applied across a range of issue areas. It also unifies the policy curriculum, offering coherence to standard methods for teaching economics and statistics, and drawing connections between fields.

The book begins by exploring the normative foundations of policymaking—political theory, social choice theory, and the Paretian and utilitarian underpinnings of policy analysis. It then introduces game theoretic models of social dilemmas—externalities, coordination problems, and commitment problems—that create opportunities for policy to improve social welfare. Finally, it shows how the political process creates technological and incentive constraints on government that shape policy outcomes. Throughout, concepts and models are illustrated and reinforced with discussions of empirical evidence and case studies.