Bayesian Social Science Statistics: Volume 2: Getting Productive

By Le Bao and Jeff Gill

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This Element introduces the basics of Bayesian regression modeling using modern computational tools. This Element only assumes that the reader has taken a basic statistics course and has seen Bayesian inference at the introductory level of Gill and Bao (2024). Some matrix algebra knowledge is assumed but the authors walk carefully through the necessary structures at the start of this Element. At the end of the process readers will fully understand how Bayesian regression models are developed and estimated, including linear and nonlinear versions. The sections cover theoretical principles and real-world applications in order to provide motivation and intuition. Because Bayesian methods are intricately tied to software, code in R and Python is provided throughout.

Format:Paperback

Language:English

ISBN:1009340972

ISBN13:9781009340977

Release Date:September 2025

Publisher:Cambridge University Press

Length:75 Pages

Related Subjects

Political Science Politics & Social Sciences

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Bayesian Social Science Statistics: Volume 2: Getting Productive

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