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OverviewIn this Element, the authors introduce Bayesian probability and inference for social science students and practitioners starting from the absolute beginning and walk readers steadily through the Element. No previous knowledge is required other than that in a basic statistics course. At the end of the process, readers will understand the core tenets of Bayesian theory and practice in a way that enables them to specify, implement, and understand models using practical social science data. Chapters will cover theoretical principles and real-world applications that provide motivation and intuition. Because Bayesian methods are intricately tied to software, code in both R and Python is provided throughout. Full Product DetailsAuthor: Jeff Gill (American University) , Le Bao (Georgetown University)Publisher: Cambridge University Press Imprint: Cambridge University Press Weight: 0.299kg ISBN: 9781009494694ISBN 10: 1009494694 Pages: 110 Publication Date: 24 October 2024 Audience: General/trade , General Format: Hardback Publisher's Status: Active Availability: Manufactured on demand  We will order this item for you from a manufactured on demand supplier. Table of ContentsReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
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