Principles Of Statistical Inference: Likelihood And The Bayesian Paradigm

Document Type

Article

Publication Date

2010

Published In

Paleontological Society Papers

Abstract

We review two foundations of statistical inference, the theory of likelihood and the Bayesian paradigm. We begin by applying principles of likelihood to generate point estimators (maximum likelihood estimators) and hypothesis tests (likelihood ratio tests). We then describe the Bayesian approach, focusing on two controversial aspects: the use of prior information and subjective probability. We illustrate these analyses using simple examples.

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