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.
Recommended Citation
Steve C. Wang.
(2010).
"Principles Of Statistical Inference: Likelihood And The Bayesian Paradigm".
Paleontological Society Papers.
Issue 16.
1-18.
https://works.swarthmore.edu/fac-math-stat/140