Making Statistics Work

At last, a statistics book that engages the philosophical foundations of probability and fully develops their implications through to practice. Clear, rigorous, and refreshingly honest about assumptions, it sets a new standard and should be required reading for anyone serious about statistics. – Aubrey Clayton, author of Bernoulli’s Fallacy: Statistical Illogic and the Crisis of Modern ScienceIn Making Statistics Work, Duncan K. Foley and Ellis Scharfenaker combine information theory, Bayesian updating, and probability theory into a single logical framework for statistical inference under imperfect and insufficient information. The authors provide many examples, making the book very accessible. This is a valuable resource for scientists, students, and teachers across disciplines. – Amos Golan, American University and the Santa Fe InstituteMaking Statistics Work introduces a robust framework that brings together information theory and Bayesian inference through entropy-maximizing priors. Offering both readability and rigor, this book is a refreshing alternative to the conventional statistical education. – Jangho Yang, University of Waterloo

Duncan K. Foley is the Leo Model Professor Emeritus of Economics at the New School for Social Research. He is the author of Understanding Capital: Marx’s Economic Theory (1986) and Adam’s Fallacy: A Guide to Economic Theology (2006) and coauthor of Growth and Distribution (second edition, 2019), among other books.

Ellis Scharfenaker is an associate professor of economics at the University of Utah. His research integrates Bayesian inference, information theory, and political economy to study industrial dynamics and income distribution.

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