<p>Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds your knowledge of and confidence in making inferences from data. Reflecting the need for scripting in today''s model-based statistics, the book pushes you to perform step-by-step calculations that are usually automated. This unique computational approach ensures that you understand enough of the details to make reasonable choices and interpretations in your own modeling work.</p><p></p><p>The text presents causal inference and generalized linear multilevel models from a simple Bayesian perspective that builds on information theory and maximum entropy. The core material ranges from the basics of regression to advanced multilevel models. It also presents measurement error, missing data, and Gaussian process models for spatial and phylogenetic confounding.</p><p></p><p>The second edition emphasizes the directed acyclic graph (DAG) approach to causal inference, integrating DAGs into many examples. The new editi
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This book is a new introduction to the history and practice of economic anthropology by two leading authors in the field. They show that anthropologists have contributed to understanding the three great questions of modern economic history: development,...
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Morality: An Anthropological Perspective provides the first account of anthropological approaches to the question of morality. By considering how morality is viewed and enacted in different cultures, and how it is related to key social institutions such...
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This accessible and authoritative overview of the subdiscipline of economic anthropology defines and frames the field for a new generation of students in search of an inspiring and fresh way of looking at the economic world.
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