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Bayesian ModelsA Statistical Primer for Ecologists$
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N. Thompson Hobbs and Mevin B. Hooten

Print publication date: 2015

Print ISBN-13: 9780691159287

Published to Princeton Scholarship Online: October 2017

DOI: 10.23943/princeton/9780691159287.001.0001

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Principles of Probability

Principles of Probability

(p.29) 3 Principles of Probability
Bayesian Models

N. Thompson Hobbs

Mevin B. Hooten

Princeton University Press

This chapter describes the rules of probability as well as probability distributions. Because models are inherently, deliberately approximate, there comes a need to understand the approximation inherent in models in terms of uncertainty. Thus, equipped with a proper understanding of the principles of probability, ecologists can analyze the particular research problem at hand regardless of its idiosyncrasies. These analyses extend logically from first principles rather than from a particular statistical recipe. The chapter starts with the definition of probability and develops a logical progression of concepts extending from it to a fully specified and implemented Bayesian analysis appropriate for a broad range of research problems in ecology.

Keywords:   probability, probability rules, probability principles, probability distributions, uncertainty, Bayesian analysis, joint probabilities

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