{"product_id":"bayesian-models-a-statistical-primer-for-ecologists-2nd-edition-9780691250120","title":"Bayesian Models: A Statistical Primer for Ecologists, 2nd Edition","description":"\u003cp\u003e\u003cb\u003eA fully updated and expanded edition of the essential primer on Bayesian modeling for ecologists\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003e\u003c\/p\u003eUniquely suited to deal with complexity in a statistically coherent way, Bayesian modeling has become an indispensable tool for ecological research. This book teaches the basic principles of mathematics and statistics needed to apply Bayesian models to the analysis of ecological data, using language non-statisticians can understand. Deemphasizing computer coding in favor of a clear treatment of model building, it starts with a definition of probability and proceeds step-by-step through distribution theory, likelihood, simple Bayesian models, and hierarchical Bayesian models. Now revised and expanded, \u003ci\u003eBayesian Models\u003c\/i\u003e enables students and practitioners to gain new insights from ecological models and data properly tempered by uncertainty.\u003cul\u003e\n\u003cli\u003eCovers the basic rules of probability needed to model diverse types of ecological data in the Bayesian framework\u003c\/li\u003e\n\u003cli\u003eShows how to write proper mathematical expressions for posterior distributions using directed acyclic graphs as templates\u003c\/li\u003e\n\u003cli\u003eExplains how to use the powerful Markov chain Monte Carlo algorithm to find posterior distributions of model parameters, latent states, and missing data\u003c\/li\u003e\n\u003cli\u003eTeaches how to check models to assure they meet the assumptions of model-based inference\u003c\/li\u003e\n\u003cli\u003eDemonstrates how to make inferences from single and multiple Bayesian models\u003c\/li\u003e\n\u003cli\u003eProvides worked problems for practicing and strengthening modeling skills\u003c\/li\u003e\n\u003cli\u003eFeatures new chapters on spatial models and modeling missing data\u003c\/li\u003e\n\u003c\/ul\u003e\u003cbr\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAbout the Author\u003c\/b\u003e\u003cbr\u003e\u003cb\u003eN. Thompson Hobbs\u003c\/b\u003e is senior research scientist at the Natural Resource Ecology Laboratory and professor emeritus in the Department of Ecosystem Science and Sustainability at Colorado State University. \u003cb\u003eMevin B. Hooten\u003c\/b\u003e is professor in the Department of Statistics and Data Sciences at The University of Texas at Austin and a fellow of the American Statistical Association. His books include (with Trevor J. Hefley) \u003ci\u003eBringing Bayesian Models to Life\u003c\/i\u003e.\u003cbr\u003e","brand":"Princeton University Press","offers":[{"title":"Default Title","offer_id":51474742313234,"sku":"9780691250120","price":62.99,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0831\/4771\/8930\/files\/img_ce1bdd72-be8d-48cf-8bd9-f0fec86058fb.jpg?v=1752579197","url":"https:\/\/surprise-castle.myshopify.com\/products\/bayesian-models-a-statistical-primer-for-ecologists-2nd-edition-9780691250120","provider":"Surprise Castle","version":"1.0","type":"link"}